1

Trainee Computer Data Scientist Jobs in Massachusetts

D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 5+ years of professional data science experience building predictive models * Expert-level knowledge of ...

Advanced degree (or proven experience) in Computer Science, Data Science, Mathematics, or any quantitative science which makes use of advanced data analytics or statistical or machine learning ...

Data Scientist

Needham, MA · On-site

$100 - $130/hr

D. in Computer Science or a related quantitative field. * 2+ years of industry experience in NLP and/or tabular data processing. * 1+ years of hands-on experience with deep learning methods.

Bayesian Data Scientist

Cambridge, MA · On-site

$90K - $210K/yr

D in Data Science, Statistics, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field * 5+ years of experience in Data Science or Analysis

Data Scientist

Boston, MA · On-site

$80 - $130/hr

Master's degree in Data Science, Computer Science, Statistics, Mathematics, or equivalent work experience. * 2+ years of hands-on experience building and deploying machine learning models using a ...

Senior Data Scientist

Boston, MA · On-site +1

$140K/yr

D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 1-2 years of professional data science experience building predictive models * Hands-on comprehensive ...

Data Scientist

Boston, MA · On-site

$123K - $129K/yr

Employer will accept a Master's degree in Computer Science, Data Science, Engineering, Marketing, or a related field and two years of experience in the job offered or two years of experience in any ...

Senior Data Scientist

Bridgewater, MA · On-site

$130 - $160/hr

D. in Computer Science, Data Science, Mathematics, Physics, Operations Research, Statistics, or a related field. * 5+ years of experience as a Data Scientist, Machine Learning Engineer, or Applied ...

Senior Data Scientist

Woburn, MA · On-site

$140K - $190K/yr

Our team consists of passionate and motivated engineers with advanced degrees in engineering, computer science, mathematics, and data science, who are seeking opportunities to use their deep ...

Data Scientist

Boston, MA · Hybrid

$123K - $129K/yr

Employer will accept a Master's degree in Computer Science, Data Science, Engineering, Marketing, or a related field and two years of experience in the job offered or two years of experience in any ...

Senior Data Scientist

Boston, MA · On-site

$100 - $130/hr

Master's in Computer Science, Statistics, Data Science, Engineering or a related field * Ph.D. is an advantage but not required Experience: * 3+ years of experience in data science or machine ...

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

Completed coursework related to Statistics, Computer Science, Machine Learning, and Data Science * Completed coursework related to Business/Management or Business/Customer Analytics Skills: * 7+ ...

Showing results 21-40

Trainee Computer Data Scientist information

What is the difference between Trainee Computer Data Scientist vs Data Analyst?

AspectTrainee Computer Data ScientistData Analyst
Required CredentialsBasic programming, statistics, entry-level data science coursesData analysis, Excel, SQL, basic statistics
Work EnvironmentLearning-focused, entry-level projects, collaborative teamsData reporting, visualization, business insights
Industry UsageGrowing in tech, finance, healthcare sectorsWidespread across industries for business decision support

The Trainee Computer Data Scientist is an entry-level role focused on developing skills in data science, programming, and machine learning, often in a learning environment. In contrast, a Data Analyst primarily handles data reporting, visualization, and basic analysis to support business decisions. While both roles require some knowledge of statistics and data tools, the Data Scientist role emphasizes advanced data modeling and programming, whereas the Data Analyst role centers on interpreting data for insights.

How to start a career in data science with no experience?

To start a career as a trainee computer data scientist with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, earning relevant certifications, and working on personal or open-source projects can demonstrate your abilities to employers. Gaining practical experience through internships or entry-level roles can also help transition into a data science career.

What are the most commonly searched types of Computer Data Scientist jobs in Massachusetts?

The most popular types of Computer Data Scientist jobs in Massachusetts are:

Principal Data Scientist

Gradient AI

Boston, MA • On-site, Remote

$190K/yr

Full-time

Posted 18 days ago


Job description

This is a fully remote opportunity with hybrid available to those local to Boston.

Gradient AI:

Gradient AI is the decision-intelligence partner for the insurance industry, giving customers an advantage in how they make decisions by revealing risk others miss and translating it into stronger performance and real-world impact. Our platform harnesses a vast industry data lake – tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals – integrating cleanly with existing workflows to make complex risk clear, usable, and actionable. Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry. We are backed by $56M in Series C funding and scaling fast – and it's an exciting time to join the team!

About the Role:

We are looking for a Principal Data Scientist with deep, specialized expertise to lead our organization's most complex and high-impact modelling and analytical initiatives. As a recognized technical authority, you will set modelling strategy across the organization, drive our most novel work, and raise the technical standard for how we build and ship models.

How you will make an impact:

  • Leverage the best of modern deep learning & large language models with traditional data science techniques to create powerful hybrid models with real uplift.
  • Brainstorm, prototype, prove, deploy, and realize the value of your work in market quickly.
  • Everything you would expect on a world-class data science team solving world-class problems. Big data. Federated learning. Unstructured data challenges. Timeseries and sequence modelling. A self-serve buffet of techniques from GLMs to XGBoost to Transformers.
  • Tell stories with your data. Inspire trust in customers, stakeholders, and prospects by turning murky math into a powerful message that drives the bottom line.

Who you are and why we want to work with you:

  • You like getting things over the line. You have an insatiable desire to deliver value now and improve next. MVP perfection is achieved not when there is nothing more to add, but when there is nothing left to take away.
  • You are not a software engineer, but you give them a run for their money. You prefer Python to R and don't understand why there is still a debate. Jupyter is a necessary evil, and you've never met a command line that scared you away.
  • You still do a better job than Claude, and you're skeptical of your friends who say they never code any more.
  • You love to take initiative and spearhead new projects, even if they are not well defined.
  • You build systems bigger than you. You contribute to open source, build packages your peers want to use, or design frameworks to elevate your team. Reuse is a strategy, not a buzzword.

Skills needed to succeed:

  • Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 8+ years of professional data science experience building predictive models
  • OR Master's or Ph.D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 5+ years of professional data science experience building predictive models
  • Expert-level knowledge of deep learning and ML algorithms and the core Python data science ecosystem. 
  • Strong communication and collaboration skills, particularly communicating with nontechnical stakeholders and leadership, and helping to pivot technical roadmaps to deliver their intended value rapidly
  • Deep experience with natural language, medical data, long-tail predictions, or similar related problem spaces
  • Strong familiarity with all phases of the MLOps model lifecycle, with experience creating team standards and practices to enforce quality and speed
  • Deep experience being accountable for model impact long term – from MLOps pipelines to monitor for drift, to KPI and impact monitoring, driving incremental and long-term improvements, triaging issues, addressing tech debt responsibly, etc.

Bonus Qualifications:

  • Fluency with actuarial methods and working with actuaries is a plus 
  • Familiarity with healthcare and medical data
  • Familiarity with underwriting and claims, or predicting long-tailed and/or rare events

What We Offer:

  • A fun, team-oriented startup culture.
  • Generous stock options - we all get to own a piece of what we're building.
  • Unlimited vacation days.
  • Flexible schedule that supports working from home.
  • Full benefits package includes medical, dental, vision, 401k, paid paternal leave, and more.
  • Ample opportunities to learn and take on new responsibilities.

We are an equal opportunity employer.

Salary Range: $190,000-235,000k base salary annually.

This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package. In accordance with the Massachusetts Pay Transparency Law, we are providing a good-faith salary range for this position at the time of posting. The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments. If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.