Best FinTech Bootcamps Detroit, MI: Find Bootcamps & Certificates

Top Detroit FinTech Bootcamps

FinTech Bootcamp Learn The Skills Guarantee™

Get the skills you need for a career in finance technology with the FinTech Bootcamp. Learn Python programming, data science, financial analysis, data visualization, and machine learning to become a Financial Analyst, Data Scientist, or Data Analyst.

Learn more & register Explore Noble Desktop’s FinTech courses
- $4,995
- 114 hours
- Free retake
- Live Online or NYC
- 1:1 Mentoring Included
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General Assembly Data Science Bootcamp

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

In-person @ 1420 Washington Blvd, Detroit, MI Also available online
- $16,450
- 12 Weeks
- Weekdays
- Intermediate
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Noble Desktop Python for Finance Bootcamp

Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling.

Available live online (virtual training) from anywhere
- $1,295
- 18 Hours
- Weekdays, Evenings, or Weekends
- Beginner
- Free Retake
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Noble Desktop Python for Data Science Bootcamp

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

Available live online (virtual training) from anywhere
- $1,495
- 30 Hours
- Weekdays, Evenings, or Weekends
- Beginner
- Free Retake
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Practical Programming FinTech Bootcamp

Learn Python for financial analysis, machine learning, and algorithmic trading from experienced finance & engineering professionals in this 60-hour immersive.

Available live online (virtual training) from anywhere
- $2,995
- 60 Hours
- See provider
- Beginner
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Practical Programming Python for Data Science Immersive

This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

Available live online (virtual training) from anywhere
- $1,495
- 30 Hours
- Weekdays
- Beginner
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University of Michigan Online AI & Machine Learning Bootcamp

Transform your career with the University of Michigan's AI & Machine Learning Bootcamp, an innovative program powered by Fullstack Academy. Over 26 weeks in a part-time, online format, this bootcamp guides students through the practical and theoretical aspects of AI and machine learning. Using real-world tools, students work on projects that apply AI fundamentals, setting them up for success in current roles or new careers in the rapidly growing field of data and AI technology.

In-person @ 500 S State St, Ann Arbor, MI
- $14,495
- 26 Weeks
- Weekdays
- Beginner
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Discover the world of FinTech, a field where finance meets technology, ranging from basic finance apps to complex cryptocurrency and blockchain technology. Learn how a FinTech bootcamp can provide the knowledge and skills for a range of careers in this growing field, including the potential salary benefits in the Detroit area.

Key Insights

FinTech merges the worlds of finance and technology, covering fields such as app development, cryptocurrency, blockchain technology, algorithmic trading, financial automation, and data science.
Attending a FinTech bootcamp equips individuals with the knowledge and skills needed for a range of career paths in the field, with a bootcamp on a resume indicating a candidate's ability to navigate complex technological areas.
The demand for FinTech literacy far outweighs the number of qualified candidates, presenting significant career opportunities for bootcamp graduates.
In Detroit, salaries for financial analysts average over $60,000. Data analysts can expect an average salary of around $65,000, while data scientists can earn over $80,000 per year.
While there are currently no schools in Detroit that offer in-person FinTech bootcamps, several online options are available, including offerings from Noble Desktop.
Choosing a FinTech bootcamp requires careful consideration of factors such as field of study, price, financing options, scheduling, mentoring, and job counseling services.

Learn more below

FinTech Topics

Python Data Science

Python is a general-purpose programming language that is known for being easily readable and visually uncluttered due to its use of whitespace to divide blocks. Used to create applications such as YouTube and DropBox, Python can be used to scrape web pages, making it a powerful tool for data analysis. Perfect for fintech startups, Python can collect and organize assembled data for analysis. Python has broad machine learning capabilities that make it agile and adaptive.

Explore Python Data Science Bootcamps

Machine Learning

Machine learning refers to the process by which a system can “learn” from experience and adjust algorithms to improve effectiveness. Used in natural language processing, computational biology, image processing, and computational finance, machine learning is a potent tool for collecting, organizing, and understanding data. FinTech startups use unsupervised machine learning to detect hidden patterns of significance in data and adjust algorithms as needed.

Explore Machine Learning Bootcamps

Financial Modeling

Financial modeling is the process by which analysts can create visual representations of business data. FinTech startups rely on financial models to create forecasts, anticipate ongoing stock performance, and make data-driven decisions. Financial analysts provide cash-flow analyses, forecast and valuation models, and other reports that inform investment decisions and policy changes.

Explore Financial Modeling Bootcamps

SQL

SQL stands for Structured Query Language. It is a domain-specific language used by fintech startups and data scientists, (along with Python and R) to manage data using relational database management systems. Using several language elements, such as clauses, expressions, queries, statements, and predicates, SQL can query data within a relational database. Fundamentally a declarative language, SQL, includes procedural elements.

Explore SQL Bootcamps

Detroit FinTech Bootcamps by School

Here are some of the top Detroit schools offering FinTech training, including General Assembly (1 course) and University of Michigan (1 course). We’ve also included 2 schools that offer live online courses you can take from anywhere, including Detroit.

Noble Desktop

NYC location: 185 Madison Avenue, New York, NY, 10016 US

Founded in 1990, Noble Desktop offers part-time and full-immersion courses on anything you can think of from design and coding to business. Located in New York City and providing courses both online and in-person, Noble Desktop prides itself on accommodating dynamic courses and bootcamps with hands-on learning, time-tested curriculums, and education from top industry experts.
Noble Desktop’s Top Live Online FinTech Bootcamps
- FinTech Bootcamp
  - 114 Hours
  - $4,995
  In this FinTech Bootcamp, participants learn how to use Python for financial analysis, machine learning and automation, and SQL. The program is taught by seasoned finance and data science professionals. Students will develop the ability to analyze financial statements, build predictive models, and work with databases. By the end of this course, newly-hired financial analysts will be prepared to succeed on the job, and aspiring financial analysts will have bolstered their resumes and technical interview skills. This course offers a free retake so students can refresh the material. It also includes one-on-one mentoring sessions.
- Python for Finance Bootcamp
  - 18 Hours
  - $1,295
  Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling.
- Python for Data Science Bootcamp
  - 30 Hours
  - $1,495
  In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.
General Assembly

Detroit location: 1420 Washington Blvd, Detroit, MI, 48226 US

General Assembly provides a variety of bootcamps and workshops in digital marketing, user experience design, and immersive courses in software engineering and data science. Students have a choice between part-time, full-time, or online classes, committed to finding you the most flexible fit for your busy schedule.
General Assembly’s Top Detroit FinTech Bootcamps
- Data Science Bootcamp
  - 12 Weeks
  - $16,450
  Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.
Practical Programming
Locations:
- NYC
- Chicago
- Live Online
Established in both Chicago and New York, Practical Programming offers online and on-site courses in Python, Data Science, Machine Learning, Web Development, JavaScript, Blockchain, and SQL.
Practical Programming’s Top Live Online FinTech Bootcamps
- FinTech Bootcamp
  - 60 Hours
  - $2,995
  Learn Python for financial analysis, machine learning, and algorithmic trading from experienced finance & engineering professionals in this 60-hour immersive.
- Python for Data Science Immersive
  - 30 Hours
  - $1,495
  This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.
University of Michigan

Detroit location: 500 S State St, Ann Arbor, MI, 48109 US

The University of Michigan, renowned for its academic excellence and innovative research, is a top-tier public university located in Ann Arbor, Michigan. It offers a diverse array of undergraduate and graduate programs across various fields.
University of Michigan’s Top Detroit FinTech Bootcamps
- Online AI & Machine Learning Bootcamp
  - 26 Weeks
  - $14,495
  Transform your career with the University of Michigan's AI & Machine Learning Bootcamp, an innovative program powered by Fullstack Academy. Over 26 weeks in a part-time, online format, this bootcamp guides students through the practical and theoretical aspects of AI and machine learning. Using real-world tools, students work on projects that apply AI fundamentals, setting them up for success in current roles or new careers in the rapidly growing field of data and AI technology.

showing 4 of 4 schools

Detroit FinTech
Corporate & Onsite Training

Upskill or reskill your workforce with our industry-leading corporate and onsite FinTech training programs. Conduct the training onsite at your location or live online from anywhere. You can also purchase vouchers for our public enrollment FinTech courses.

corporate@nobledesktop.com (212) 226-4149

FinTech Training Locations in or Near Detroit

Find an in-person class in Detroit. We found 2 schools offering face-to-face training and 1 offering live online FinTech courses.

Learn FinTech for a New Career

FinTech is one of the core skills needed to secure one of these positions. See the career pages for more information on required skills, tips for landing a job, typical day-to-day work, and where to find job postings.

Financial Analyst

Salary in Detroit

$81,000 / year
5.11% more than the U.S. average

Financial analysts use their business, finance, or accounting background to analyze data and make recommendations for investments. They study past, present, and future business and economic trends to provide data-driven insights for business decision-making. Financial analysts take on roles as fund managers, portfolio managers, investment advisors, and risk analysts. Many earn additional credentials in the field, such as Certified Public Accountant or Project Management Professional certifications.
Learn about becoming a Financial Analyst
Data Scientist

Salary in Detroit

$110,000 / year
10.23% less than the U.S. average

Data scientists collect, organize, and analyze large sets of data, providing analysis that is key to decision making. Governments, non-profits, and businesses of all types rely on data for forecasting, risk management, and resource allocation. Data scientists discover and analyze trends in data, and report their findings to stakeholders. They will use algorithms and models to simplify and mine data sets to create data-driven recommendations. Data scientists are needed across a handful of industries, especially the ubiquity of data and the reliance on it for business decision-making.
Learn about becoming a Data Scientist
Software Engineer

Salary in Detroit

$85,000 / year
18.24% less than the U.S. average

Software engineers use their extensive knowledge of user experience design, operating systems, and programming languages to develop software. They can create different types of software, from games to operating systems. After analyzing a client's needs, they design, develop, and test software to meet that need. Software engineers can be divided into two distinct career categories: application engineers and systems engineers.
Learn about becoming a Software Engineer
Python Developer

Salary in Detroit

$139,000 / year
3.94% more than the U.S. average

Python Developers typically choose to focus on back end web development, data science or analysis, scripting, or product development. They build the server side of websites, processes for data analysis, and create automation scripts.
Learn about becoming a Python Developer

showing 4 of 4 career paths

Indeed.com salary data from November 2024

Learn More About Detroit FinTech Bootcamps

Detroit is rising to challenge the world’s strongest FinTech regions. This city is regularly ranked among the top ten in the United States for banking-related talent, growth in financial services jobs, and emerging FinTech industries. It also hosts the two largest mortgage providers in the U.S., Rocket Mortgage and United Wholesale Mortgage, companies built on their strength with online financial services. Several industry groups and nonprofits foster the growth of FinTech companies in Detroit, including the Detroit FinTech Association, Detroit FinTech Bay, Detroit Labs, and the Detroit FinTech Challenge. The city’s historically strong educational base further boosts local FinTech companies by preparing skilled workers; these FinTech graduates will find ample employment opportunities nearby.

What is FinTech?

FinTech refers to any technology created and used for financial activities. These technologies can be applications (mobile, web-based, or desktop), servers and databases, programming languages, or integrated systems incorporating multiple tools. FinTech also refers to the services provided through these technologies and the businesses that create and offer such products and services. Consumers and businesses alike use FinTech to manage accounts, transactions, budgets, and investments.

FinTech has grown rapidly in recent years, but its origins date back to the inventions of credit, wire transfers, and credit cards, which separated financial transactions from physical currency. Online banking originated in the 1980s but was not widely adopted until the late 1990s, aided by improvements in Web technologies. The widespread adoption of smartphones further accelerated FinTech via mobile applications.

Some examples of now-established FinTech applications and businesses:

Point-of-sale systems - Square
Payment services - PayPal and Venmo
Cryptocurrency generation and trading - Bitcoin
Credit reporting and consulting services - Credit Karma
Online, virtual, and automated:

Banking - Chime
Investment advising and portfolio management - Wealthfront
Lending - Upstart
Stock trading - Robinhood

Innovations like artificial intelligence, machine learning, blockchain technology, and novel digital interfaces continue to further expand the definition and utility of FinTech.

What Can You Do with FinTech Training?

Most FinTech solutions are collaborative efforts requiring a combination of end-user software, internal data management, security features, and interfaces with financial institutions. In addition to FinTech companies that directly offer services, banks and other traditional financial businesses incorporate FinTech features. Within all these structures, FinTech designers and programmers can create multiple useful tools. The most familiar FinTech applications are online and mobile banking and investment services. FinTech also includes digital services for making and requesting loans, crowdfunding projects, managing payments, and adding embedded finance (financial features within non-financial services). In addition to the innovators who design and build these systems, businesses need employees to monitor their activity, maintain their security, promote them, teach customers how to use them, and manage their legal concerns. FinTech training helps professionals in adjacent fields understand FinTech’s features, opportunities, and concerns.

Personal FinTech applications are less common, although some possibilities exist for tech-savvy creators. Individual programmers or startups can write small-scale financial enterprise applications, especially as mobile apps. These programs can offer familiar functions like budgeting, investment tracking, or sales management, or can serve novel functions not available through other platforms.

Training in FinTech can also teach people how to use these technologies to their full extent and incorporate FinTech into their personal and professional activities. Individuals can use FinTech apps to track their savings and spending and manage retirement planning and other investments. Freelance financial advisors and consultants can augment their practice with FinTech and direct their clients to useful tools. Artists, crafters, and other creators can find success through direct sales and crowdfunding platforms. Retail sellers benefit from point-of-sale, insurance management, and budgeting applications. Entrepreneurs can secure funding for their projects and manage costs better using FinTech products.

What Will I Learn in a FinTech Class?

Finance

To apply technological tools to a field like finance, students must have a working knowledge of that field. Finance applies broadly to anything monetary, including valuation, transactions, and economics. The amount of financial education varies between FinTech classes. Some classes include detailed lessons on financial analysis and forecasting, some give a brief introduction to financial fundamentals, and some provide little or no direct financial education, assuming this as background. Still, any FinTech class must address the underlying principles that its algorithms represent and manipulate, and the more students learn about finance, the better they can understand and apply FinTech.

Financial Modeling

Financial modelers create detailed financial representations of business entities, recording their assets, expenses, and earnings both to describe that business’ current state and to guide its future activities. Financial modelers apply principles of accounting, finance, financial analysis, and business consulting to generate predictions based on a business’ options. A financial model can help business owners understand their operations better, predict the results of corrective measures, and anticipate risks. Many FinTech products and services incorporate financial modeling, basing their predictions and advice on a user’s existing financial records plus analyses generated from broader financial data. Other FinTech systems create models to represent whole industries or markets and project the effects of changes upon these complex systems.

Data Science

A broad field incorporating many skills, tools, and approaches, data science studies the use of data to create knowledge. Data science uses methods from scientific inquiry, mathematics, and computer science to gather, filter, store, protect, reformat, analyze, describe, and query information. Data science also addresses the nature of data, how to maintain its accuracy (especially over huge datasets), and how to draw appropriate inferences from available information.

FinTech uses data science methods to represent and process financial information. Data collection and storage are necessary not only for individual financial records but also for the widespread financial data used to describe and predict economic trends. Data analysis and reporting methods create views that make complex financial information accessible to users. Creating any FinTech product requires proficiency in data storage, manipulation, and presentation, along with fluency in the programming languages and structures used for these tasks.

Financial Analytics

Financial analytics is the application of data analytics to financial information. Financial analyses might examine amounts and transactions from accounts, sales, expenses, stocks, interest, taxes, or tariffs. These analyses help both individual consumers and businesses understand their financial activity and make informed decisions about financial choices. Many FinTech products and services incorporate financial analytic methods to illustrate monetary information and guide their users. To create these tools, FinTech designers and workers need to understand their underlying techniques. Being trained as a financial analyst and advisor also helps a FinTech designer understand the kinds of analyses and reports that will best benefit their users.

Software Development

Software development includes the programming skills required to create applications, the ability to design useful and effective programs, and the skills to coordinate software development across a team. Almost all FinTech products are applications or incorporate software as part of a broader system. FinTech workers writing these applications will need to study one or more programming languages, particularly languages frequently used for data processing like Python, SQL, Java, and Ruby. Workers in other areas of FinTech also need to understand general computer science and software development processes.

Machine Learning

Machine learning is the use of automated programs to gather data, analyze it, and apply the resulting knowledge to further investigations and problem-solving activities. Rather than solely describing data to users, machine learning systems search for patterns and change their behavior based on their observations. Machine learning algorithms can collect financial data, map its trends, and then use this knowledge to guide users’ decisions or directly initiate transactions. With the right interfaces, machine learning systems can make sales and purchases, observing the results of their actions and finding optimal behavior patterns. FinTech workers trained in machine learning techniques can create automated stock managers, financial advisors, and detailed, dynamic financial models.

Blockchain and Cryptocurrency

Blockchain technology represents data in distributed, linked blocks across nodes in a computer network. This structure makes stored data more resistant to change, whether from errors or tampering, and ensures its security and longevity. In finance, blockchain is best known for its use in cryptocurrency, virtual currencies represented and secured by complex codes, aka cryptography. Cryptocurrency is one of the purest forms of FinTech: money that exists totally within digital technologies, enabling faster, cheaper, more secure transactions. Blockchain also enables certain kinds of FinTech and makes most FinTech faster and more secure. Most FinTech classes will explain blockchain and cryptocurrency well enough that students can understand these concepts and their general interactions with FinTech. Some applications of FinTech require students to actively work with blockchain structures, either using them within their own projects or interfacing with them for transactions.

How Hard is it to Learn FinTech?

FinTech is a broad field; mastering it fully could require several graduate degrees. Most professionals who create FinTech systems focus on one subfield such as programming, financial modeling, or financial analysis, sharing their expertise in teams. However, there are some core concepts every FinTech professional should know. An introductory course can teach these fundamentals in a few weeks, but applying these principles to specific technologies is more challenging and requires further education. FinTech workers should be comfortable with mathematics (especially statistics), should understand the principles of computer science and coding, and should learn as much as possible about finance, from individual budgeting and investing to business management and economics. Certain of these subjects may be more difficult for a given student to master depending on their experience, prior study, and aptitude.

What are the most challenging parts of learning FinTech?

Finance is a complex subject, but the core financial knowledge required to work in FinTech is manageable for most students. What challenges FinTech students more are the technical skills used to build digital products and services, the mathematical skills to make these tools efficient and accurate, and the creativity to envision new approaches and solutions.

Technologies and tools

Programming languages, including general-purpose languages like Python or specialized data management languages like SQL, create FinTech applications and systems.
Software tools empower many FinTech services and include databases, data visualization programs, and biometric recognition systems.
Modern FinTech is built on computing paradigms that transcend specific languages or programs, such as blockchain and machine learning.

Mathematics

FinTech professionals need a strong grasp of statistics and general mathematics to work with detailed financial models and analyses, comprehend their underlying structures, and construct appropriate equations.

Creativity and innovation

Creating genuinely new contributions to FinTech requires a thorough understanding of the field, the insight to spot unsolved problems, and the creativity to find their solutions.

How Long Does it Take to Learn FinTech?

Few experts have learned every aspect of FinTech, especially given the field’s rapid expansion. An in-depth study would take multiple courses and years of work experience. An increasing number of universities offer degree programs in FinTech, which require two to six years of study. A more manageable goal is to learn enough about FinTech to work in the field. A FinTech bootcamp that teaches enough for entry-level employment might take from one to three months if pursued on a full-time schedule. A more thorough professional training program including classes on data science, financial analysis, financial modeling, and the common technologies used in FinTech will average six months of full-time study but will qualify its graduates for more jobs. If a worker already possesses professional ability in a related field like software development, web development, or financial analysis, a short introductory class in FinTech, perhaps a week or two long, might provide them with the necessary knowledge to transition into this field.

Should I Learn FinTech In Person or Online?

Traditional in-person study offers the fastest, most direct interaction with an instructor. Some students prefer in-person classes due to learning, attentional, or sensory difficulties that make online studies less productive. A shared classroom site also simplifies access to computing hardware, software, and printed materials. However, in-person study includes travel time and expenses, and some students have no suitable school in reach. Even for students with FinTech classes nearby, restricting themselves to in-person classes greatly reduces their options for class formats, instructors, and scheduling.

Online learning removes the limitations of location, multiplying students’ choices. Students can access online classes from anywhere with a decent Internet connection. For some students, this convenience and comfort improve their learning. However, online students must maintain computer access and manage all software themselves. Fortunately, most online classes include discounted or free software downloads, and most FinTech classes use open-source tools. Live online classes, presented through streaming video services like Zoom, allow real-time interaction between students and instructors. By comparison, self-paced online courses use pre-recorded and written lessons. While self-paced classes greatly reduce instructor access, they do permit students to study on a more convenient schedule. Online classes, especially self-paced ones, may also be supplemented by message boards, chatrooms, downloadable texts, and interactive websites. Of the two, live courses usually offer the most current information, since self-paced courses are updated less frequently.

Can I Learn FinTech Free Online?

Free FinTech lessons are available from several online sources, in both text and video formats. Social media sites like YouTube host many video lessons about FinTech, although these lessons vary in quality depending on their creators. Channels from educational providers like Noble Desktop are generally more reliable. Some online schools, including Coursera, Class Central, and edX, host free lessons about FinTech on their sites. A few sites, such as the Centre for Finance, Technology, and Entrepreneurship (CFTE), even offer free FinTech certificate programs.

Free lessons are particularly useful as an introduction to explain the tools and techniques of FinTech and help students decide if they want to pursue further study. However, free lessons rarely cover enough content to prepare students for entry-level employment, much less provide a complete education in any subject. Teaching sites often limit their free lessons to encourage visitors to purchase a full course. Even complete certificate programs usually reserve their study projects, interactive features, and instructor assistance for paid subscribers. Further, free lessons offer only pre-recorded material, which lacks an instructor’s full expertise and limits the currency of that curriculum. Finally, free lessons provide little feedback, slowing students’ work and leaving them uncertain of their progress. Paid, guided instruction is generally necessary to learn enough about FinTech for professional use or employment.

What Should I Learn Alongside FinTech?

Most complementary skills for FinTech follow its two components: finance and technology. FinTech classes include financial theory and practice, but these concepts and techniques can be addressed in more depth. Similarly, courses that teach technical skills for FinTech cannot cover every possible subject.

Finance

Accounting - how to maintain personal, business, and financial institution accounts, including topics like asset depreciation, taxes, cash flow, and auditing
Economics - understanding and modeling the forces that affect large-scale financial activities and their effects on individual actors, businesses, industries, markets, and governments
Financial Law - legal concerns and practices that apply to financial activity, including consumer protections, fraud prevention, financial regulations, and dispute resolution
Financial Advising - consultation practices that improve clients’ financial behaviors and outcomes, including analysis, guidance, and support services
Other financial subjects that could be beneficial include: Taxation, Investment, Risk Management, Real Estate, and Financial Ethics

Technology

User Interface (UI) and User Experience (UX) Design - practices that improve the usability and appeal of products, particularly digital products like software and websites
Digital / Social Media Studies - understanding the use of online services and interactions
Web Development - creating webpages, websites, and servers, as well as implementing FinTech products as web-based applications
Mobile Development - designing and writing applications for mobile devices
Cybersecurity - protecting records, transactions, and transmissions from inspection or alteration by unauthorized actors
Programming Languages - coding in various languages like Python, Java, Ruby, or SQL that are used to create FinTech products
Other technical skills that are valuable to combine with a FinTech education include: Machine Learning, Data Visualization, Artificial Intelligence, and Cloud Computing

Other Valuable Skills

Communications - the ability to explain complex financial concepts, make them accessible to users, and create informative technologies
Marketing - skills that help FinTech creators shape their offerings to customer needs and convince users to engage with their products
Management - especially project management, the ability to coordinate workers with differing specialties to produce complex products without wasting effort

Industries that Use FinTech

Detroit aspires to become a global hub for FinTech, with a growing number of local FinTech companies and support to attract more. With local giants like Rocket Mortgage and United Wholesale Mortgage, lending and banking lead among FinTech employers. Other financial services, including consulting, advising, investment, and debt management, have also largely shifted to FinTech models. Using these convenient tools, other industries with embedded financial components have incorporated FinTech; prominent examples include real estate, insurance, and retail sales. Some businesses in these industries use FinTech and other digital tools to operate entirely online.

Banking

Banks were the first adopters of early FinTech, first using the telegraph to create a network of ‘wire transfers’. As new FinTech emerges, banks quickly incorporate these tools to better serve current customers and attract new ones. Web-based online banking expanded rapidly in the 1990s and eventually became customers’ primary means of interacting with their accounts. In the last two decades, mobile banking has overtaken Web-based services. In addition to displaying account information and enabling standard transactions like transfers and bill payments, FinTech applications process loan applications and automated approvals, virtual payments, and investments. Some ‘banks’ are now entirely virtual, with no branch locations. Using cryptocurrency, some of these banks even operate without physical collateral. FinTech workers in Detroit can find employment directly with local banks like First Independence Bank and with companies like Bankjoy that provide technology services for banks anywhere in the world.

Ally Financial, Inc., based in Detroit and specializing in automotive financing., is a prominent example of a fully digital bank and lender. As no surprise given Detroit’s manufacturing history, one of its strongest FinTech sectors is in vehicle financing, investment, and insurance. RouteOne, for example, connects automotive dealers, customers, and lenders to simplify the financing process. Other examples of FinTech related to banking include credit lenders like Detroit-based Credibly, credit monitoring services, payment processors like Autobooks, and investment portfolio management. Many of these companies are based purely in FinTech, providing novel technological solutions to financial challenges.

Real Estate

Real estate overlaps multiple areas of finance. Naturally, the financial industry most closely associated with real estate is mortgage lending. Detroit boasts two of the world’s largest online mortgage companies, Rocket Mortgage and United Wholesale Mortgage. Another mortgage lender, AmeriSave, is another major local FinTech employer. The real estate industry also uses FinTech tools to determine property values, track markets, anticipate opportunities and risks, advise buyers and sellers, and process transactions, not just for home sales but also for their associated services and fees. FinTech also overlaps with PropTech, technological solutions for property management, including construction, repair, renting, and housing investment. Thus, FinTech workers may provide solutions for real estate companies, work directly within large property management companies, or adapt their skills to create similar tech solutions for real estate concerns.

Financial Advising / Consulting

Rather than primarily handling financial accounts, another set of industries assists customers with their financial challenges by providing analysis, advice, planning, and access to investors. Financial advising and consulting existed before FinTech but were greatly improved and expanded by technology. Other adjacent financial services emerged entirely thanks to FinTech. These financial businesses include services for large corporations, small startups, and individual entrepreneurs and investors. For individual consumers, Detroit companies Pocketnest and Greenpath offer “financial wellness coaching,” online guidance for personal accounting, debt management, and investment savings. Another area FinTech company, Cowen, Inc., provides financial advising and investment assistance for both individuals and businesses. Rather than advising clients, Benzinga reports financial news and provides ongoing analyses of economic trends.

These prominent FinTech companies employ a significant proportion of the technical talent not taken by banks and other financial institutions. More traditional financial advising and consulting companies also need FinTech workers to manage their online operations and incorporate new FinTech offerings as they emerge.

Retail Sales

Certain FinTech tools are geared toward consumer sales, including point-of-sale systems, inventory management systems, automated purchasing tools, and expert systems that track purchasing behavior. For example, Detroit company North provides payment processing and related services for over 350,000 merchants across the U.S. An increasing number of retailers exist entirely online, their operations managed through virtual storefronts and digital tools. In addition to the FinTech companies that assist these retailers, larger retailers build and maintain financial technologies “in-house”, including not only storefronts and inventory databases but also credit accounts and loyalty programs. FinTech workers may create products specifically for retailers or may be hired by resellers to manage their tech systems.

Insurance

Being closely related, insurance companies employ many of the same technologies as financial services. Insurance is a major component of financial risk management, and insurers perform similar determinations of value and expense. Insurance can also overlap other industries; for example, Detroit’s CoverTree offers online insurance services for manufactured homes. Fortegra Financial is another regional employer combining FinTech with insurance. Insurance companies can integrate FinTech with their online services in several ways, such as advising customers about their insurance needs, estimating value, managing policies, and processing sales. Internally, FinTech tools help insurers forecast markets, estimate liabilities, and set rates. Insurance companies may hire FinTech workers to create such financial tools or adapt their technical skills to create similar systems more specific to insurance (InsurTech).

FinTech Job Titles and Salaries

Data Scientist

Finance and technology intersect in data. Data Scientists study data and create reliable, accurate, and secure systems for its collection, storage, revision, analysis, and reporting. Within FinTech, Data Scientists are data experts who describe the technical needs of financial services, such as storage space, processing power, and security concerns. Data Scientists also advise FinTech companies creating analysis tools and help to design financial interfaces to improve their usefulness. The average annual salary for Data Scientists in Detroit, across all positions, is $110,000. An entry-level Data Scientist in Detroit starts at an average of $86,000 per year.

Financial Analyst

Financial Analysts apply data analysis to financial information. They are often trained in financial modeling, valuation, economics, and/or accounting, using data analysis methods to build large-scale systems for these functions. In FinTech, financial analysts assist in developing software tools that perform automated analyses for users or use these analyses to power other financial applications. They also lend their financial expertise to guide the development of FinTech services. Other Financial Analysts use FinTech’s ability to collect and translate massive quantities of financial data to empower their consulting services and more accurately advise clients. Financial Analysts in Detroit earn an average of $82,000 annually, though this average includes self-employed consultants. Entry-level Financial Analysts in Detroit start considerably lower, at $29,000 per year.

Security Analyst

FinTech relies on its ability to store, update, and transfer financial information without error, loss, or interference. Without data security and the trust of its users, FinTech cannot exist. Security Analysts examine systems, including software and data management systems, to anticipate security risks and create protective measures. In FinTech, Security Analysts reduce risks from problems like technical errors, data leaks, malware, cyberattacks, identity theft, and fraud. Security Analysts in Detroit earn $49,000 per year on average, again including freelance analysts and consultants.

Software Engineer

A Software Engineer or Software Developer creates complete software products or component code for mobile, web-based, or desktop applications. In FinTech, Software Engineers implement the ideas of financial experts and analysts, writing programs to perform requested functions. Software Engineers and Developers often work in teams with project managers, financial experts, and data scientists to develop new FinTech services. They may also maintain and update existing systems within FinTech companies. In Detroit, Software Engineers earn an average of $86,000 annually, with entry-level Software Engineers starting at $57,000 per year.

Machine Learning Engineer

Machine learning algorithms find patterns in large data sets and use this information to refine later searches, create analyses, and create responses to user inquiries. In FinTech, Machine Learning Engineers design and train these algorithms to examine financial data, identifying patterns that guide users, suggest opportunities, and improve existing financial systems. Some FinTech products are learning systems trained on financial information from their users, while others use learning systems to perform automated functions like tracking stocks and making well-timed transactions. Thanks to high demand and their rarer technical expertise, Machine Learning Engineers in Detroit earn an average of $144,000 annually.

FinTech Classes Near Me

In addition to live online courses, New Horizons presents professional skill training classes at locations around the U.S., including a campus in Livonia, MI. Financial workers seeking valuable tech skills can learn to code in Python and SQL, languages popularly used for data management and analysis. New Horizon’s most directly relevant course is Python for Finance, a three-day course for students already familiar with Python and ready to apply the language to financial models and analyses. This course begins with lessons on Python’s NumPy, Pandas, and Mathplotlib libraries, and then demonstrates how to apply functions from these libraries to represent financial data and create algorithms for financial modeling, analysis, and automated transactions. Students also learn how to use QuantConnect, an open-source algorithmic trading platform, to perform many of these same operations.

General Assembly hosts intensive bootcamps in coding and other technical skills at locations in multiple cities including Detroit. Their Data Science Bootcamp is also a professional-level certificate course that prepares students for work in data science and related fields like FinTech. This intermediate-level course requires some background in mathematics (particularly statistics) and coding (primarily the Python programming language), but the school provides access to online preparatory classes in these subjects for students who need them. The 12-week bootcamp also teaches data management with SQL; data structures, analyses, and visualization in Excel; and Tableau and Power BI for more advanced reporting methods. Students practice data science methods with practical projects that can be used to create a starting portfolio, including a comprehensive capstone project. Another General Assembly bootcamp course, Data Analytics Bootcamp, focuses more strongly on data analysis and is valuable training for students interested in the financial analysis aspects of FinTech.

Live online classes from Wall Street Prep cover a wide range of financial career skills. While designed to prepare students for work in the financial services industry, these courses can also teach technology workers interested in financial applications. The most applicable of these courses is their Financial & Valuation Modeling bootcamp, an intensive certificate course taught in three full-day classes: Financial Statement, Discounted Cash Flow (DCF), and Mergers & Acquisitions (M&A) Modeling. Since the course presents these models primarily in Excel, prior Excel experience is a prerequisite, but course enrollment includes access to a self-guided Excel Crash Course. After completing the bootcamp, students retain access to class lectures and materials, plus lessons on Comparables and Leveraged Buyout (LBO) Modeling.

American Management Association offers multiple live online short courses in financial topics. Their catalog includes courses at several levels of instruction, the most basic being Fundamentals of Finance and Accounting for Non-Financial Managers. In three to five sessions (depending on schedule), this course gives novices a functional background in financial concepts and accounting methods, enabling them to understand these subjects and determine their further educational needs. This school also offers training seminars in Financial Analysis and Financial Forecasting. While these are not full professional training courses and are primarily designed for managers who need to understand these fields for their business operations, these classes are also useful for technology workers interested in applying their skills to finance.

Noble Desktop offers live online training courses including career-oriented professional training programs and bootcamps. Their primary FinTech course is FinTech Bootcamp, an intensive program covering several technical skills and their applications to financial products. The course primarily uses Python, a general-purpose programming language, to write programs and demonstrate their financial applications. No prior knowledge of Python, programming, or data science is required, but participants should have some financial background, enough to be familiar with concepts like Net Present Value (NPV), Internal Rate of Return (IRR), and stock trading. The bootcamp’s core curriculum consists of five units, each of which is also available as a separate, stand-alone bootcamp course: Python for Data Science, SQL (a specialized language for data management), Python for Automation, Python Data Visualization & Interactive Dashboards, and Python Machine Learning. These core units take about four weeks to finish on a full-time schedule or four months of part-time study. Students then receive their choice of two out of three bonus electives (each also available as a separate bootcamp): Python for Finance, Financial Modeling, or Python for AI: Create AI Apps With Flask & OpenAI. The course includes several projects suitable for a starting portfolio, plus six 1-on-1 mentoring sessions usable for career planning and preparation. Students also receive supplemental study materials and access to class recordings and can retake the class once for free for up to one year.

FinTech Corporate Training

Noble Desktop provides FinTech classes for businesses and other organizations, teaching existing classes from their catalog or creating custom courses to meet specific needs. For example, companies can book an introduction to FinTech, a more in-depth bootcamp covering multiple FinTech topics, or a course on a related skill like Financial Modeling or Data Analysis. These classes can be joined live online or hosted onsite at your location. Class schedules can also be adjusted as necessary. As another alternative, you can purchase vouchers for existing live classes, with a discount for bulk purchases. Employees with these vouchers can then book the designated classes to fit their schedules.

For a free consultation to address your questions, plan a custom course, schedule classes, or purchase bulk class vouchers, contact corporate@nobledesktop.com.

About the Author

Nathan Large has written in multiple technical and creative formats across careers as a behavioral researcher, educator, content creator, tabletop game designer, book editor, legal proofreader, author, live storyteller, and poet. After completing his doctorate in cognitive psychology at SUNY Buffalo, Nathan moved to Erie, PA, and began offering freelance writing and editing services. He learned desktop publishing and graphic design while creating a series of self-published science-fiction novels and two original card games. Most recently, he served as a quality control reviewer for mortgage documents.

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