Dive into the journey of becoming a data scientist, from initial exploration to securing an entry-level, mid-level, or senior position in the field. Explore the roles and responsibilities at each level, and understand how further training and education can enhance your career prospects.

Key Insights

  • The path to becoming a data scientist begins with exploring the field, understanding job prospects and salary expectations, and identifying the skills and qualifications necessary for the role.
  • Aspiring data scientists can gain essential skills through online or in-person classes, focusing on areas such as data science fundamentals, data visualization tools, machine learning, and programming languages such as R, Python, Java, and SQL.
  • Internships provide valuable professional experience, hands-on learning opportunities, and networking possibilities in the data science field.
  • Entry-level data scientist jobs often involve meeting with stakeholders, developing data cleaning code, verifying data, and improving data process efficiency.
  • Mid-level data scientist roles may require researching and developing analytical solutions, managing data analysis project lifecycles, and developing machine learning algorithms.
  • Senior data scientist roles demand high levels of expertise to extract and model data, deploy machine learning models, establish health metrics, and identify patterns to meet organizational goals.

If you are interested in starting a career in data science, you might wonder what the Data Scientist career path looks like. How does one become a Data Scientist? What can one expect from an entry-level Data Scientist role? What industries do Data Scientists work in? What does it look like to advance from one Data Scientist role to another? The following sections will examine how to learn more about data science as a career, what to expect at entry-level, mid-level, and senior-level positions, and how to have a successful career as a freelance Data Scientist.

Getting Started

To discover if the role of Data Scientist is right for you, you can read about data science careers, interview Data Scientists working in the field, attend free introductory classes, learn about projected job growth in this field, learn the average salary you can expect to make as a Data Scientist, discover the requirements to become a Data Scientist, and more. Noble Desktop’s Data Science Learn Hub provides information on this career path, breaks down the different ways you can learn essential skills to become a Data Scientist, links to free resources you can use to start learning, and more.

Do I Need a Degree to Become a Data Scientist?

If you are interested in a data science career, you might wonder if you need a degree to become a Data Scientist. Data Scientists have a thorough understanding of mathematical and scientific principles including statistics, linear algebra, calculus, statistics, probability, computer science, and certain programming languages. With the rising use of artificial intelligence (AI), Data Scientists should also understand machine learning algorithms and their uses as this branch of AI plays an increasingly crucial role in gathering, sorting, managing, and analyzing data. While most Data Scientists hold a four-year college degree of some kind, often in a subject such as computer science, there are other ways besides university to learn the necessary skills required of a Data Scientist.

You can learn the skills needed to start a career as a Data Scientist by attending in-person or live online data science classes. Such classes may include training on data science fundamentals, the use of data visualization tools, and the use of machine learning. Data Scientists should also understand the programming languages R, Python, Java, and SQL, so classes that provide hands-on experience with these programming languages will greatly benefit aspiring Data Scientists. Some courses focus on specific skills while others, such as certificate courses, cover a range of skills and topics.

Read more about if you need a degree to become a Data Scientist.

Data Science Certificate: Live & Hands-on, In NYC or Online, 0% Financing, 1-on-1 Mentoring, Free Retake, Job Prep. Named a Top Bootcamp by Forbes, Fortune, & Time Out. Noble Desktop. Learn More.

Internships

Internships, either paid or volunteer, can help to add professional experience to your resume, provide hands-on experience, and build connections among professionals in the field. Data Scientists who complete an internship can add projects from the internship to their professional portfolios and use managers or mentors from the internship as professional references. You can find data science internships through employment websites such as Indeed, LinkedIn, and Glassdoor. Colleges, universities, and educational data science programs may also have partnerships with or connections to companies with student internships.

Entry-Level Data Scientist Jobs

Entry-level Data Scientist job titles include: 

  • Junior Data Scientist 
  • Clinical Data Coordinator
  • Associate Data Scientist
  • Data Science Associate
  • Entry-level Data Science-Analyst

Responsibilities may include: 

  • Meeting with and communicating findings to internal stakeholders
  • Work cross-functionally with developers, product managers, management, and product owners to identify requirements, gather data and insights, and make recommendations for improvements and opportunities.
  • Develop code for cleaning data
  • Develop models for gathering data and extracting valuable information
  • Review and improve models
  • Verify data
  • Identify and remedy issues concerning data processes
  • Report data trends and metrics
  • Perform database testing
  • Import data from various sources
  • Improve efficiency of processes
  • Design and develop models and algorithms for managing large data sets and creating business insights

Mid-Level Data Scientist Jobs

Mid-level Data Scientist job titles include: 

  • Computer Scientist
  • Data Scientist - Mid Level
  • Biological Data Scientist
  • Product Data Specialist
  • Data Scientist (Mid)
  • Data Science Consultant Level 2
  • Data Science Manager

Common responsibilities one can expect as a mid-level Data Scientist include:

  • Engage customers to understand their analysis needs
  • Research, develop, and test analytical solutions to solve complex problems
  • Work with developers to build analytic software, integrate simulation, modeling, and analysis frameworks
  • Capture data from various sources and extract valuable insights
  • Manage the data analysis project lifecycle from start to finish
  • Develop analytical methods for identifying, collecting, and analyzing large data sets 
  • Develop machine learning algorithms
  • Build reports, charts, and dashboards
  • Coordinate with teams to implement data-gathering models

Senior Data Scientist Jobs

Senior-level Data Scientist job titles include: 

Senior Data Scientists have several years of professional experience in data science. They use their expertise to: 

  • Extract, process, and model data
  • Develop short and long-term forecasts to help organizations plan
  • Deploy machine learning models
  • Work with stakeholders to refine data-gathering processes
  • Establish health metrics to gauge the effectiveness of efforts
  • Acquire data and extract valuable insights
  • Use coding and big data best practices
  • Prepare data
  • Make recommendations to internal stakeholders
  • Identify patterns and opportunities to meet the organization’s goals 

Another Path: Freelancing

What if you want to be a freelance Data Scientist? You can start your career as a Data Scientist freelance by posting your professional portfolio to sites like Upwork, Fiverr, and Toptotal.com. Freelance careers work well for those looking to have a flexible schedule, be self-employed, gain extra income on the side, or build experience before finding a full-time job. Learn more about freelancing as a Data Scientist.

How Do I Find A Data Scientist Job?

Data Scientists can find work in corporations, medicine, academia, government organizations, nonprofits, startups, and more. Most Data Scientists work full-time for an organization, either remotely or in a traditional office. However, some Data Scientists find freelance or part-time work. The development of a professional portfolio highlights your abilities no matter which career path you choose.

Data plays a critical role in understanding the current state of an organization and in identifying opportunities for growth. Data Scientists can therefore find careers in many fields and have many options when it comes to the type of organization they wish to work for. But you may wonder how to find these Data Scientist jobs. Data Scientist jobs are posted on popular sites such as Indeed, LinkedIn, Google Jobs, Glassdoor, Stack Overflow, Startupers, Amazon Jobs, and more. You can search these sites for new postings or set up email alerts for keywords and job titles related to data science.

Most of these job postings pertain to full-time roles, so how might you go about establishing a freelance or part-time career as a Data Scientist? You can start your journey as a Data Scientist freelancer by posting your portfolio to the following sites: 

  • Upwork.com
  • Fiverr.com
  • Toptotal.com

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.

Key Takeaways

  • Data Scientists typically advance from an entry-level position to a senior position as they gain experience.
  • The key difference between entry-level, mid-level, and senior-level positions are the number of years the Data Scientist has. More senior positions may also be entrusted with management or consulting responsibilities, in addition to performing more advanced tasks.
  • You can receive comprehensive training to become a Data Scientist through an in-person or live online course with Noble Desktop.