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Computer Science Data Science Jobs in Cambridge, MA

D.) in Computer Science, Data Science, Artificial Intelligence, or a related field. • Minimum of 10 years of experience in data science, AI, or related fields, with at least 5 years in a leadership ...

Required : • Advanced degree in Computer Science, Engineering, Statistics, or related field • Minimum of 10 years of experience in data science, with 6 years of experience in the pharmaceutical ...

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field ... Established product data science roadmap aligned with business priorities; shipped at least one ...

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

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

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

The Director, Data (MarTech) is responsible for applying data exploration and visualization ... Bachelors in Computer Science, Statistics or any related field with an applied quantitative and ...

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Computer Science Data Science information

See Cambridge, MA salary details

$41K

$134.2K

$214.8K

How much do computer science data science jobs pay per year?

As of Jun 23, 2026, the average yearly pay for computer science data science in Cambridge, MA is $134,150.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,700.00 and $148,600.00 per year, depending on experience, location, and employer.

Can a computer scientist work in data science?

Yes, computer scientists often work in data science because they have strong programming, algorithms, and analytical skills essential for data analysis, machine learning, and statistical modeling. Many data scientists have backgrounds in computer science and use tools like Python, R, and SQL to analyze large datasets and develop predictive models.

Is 40 too late for data science?

Computer Science Data Science is a field where individuals can enter at any age, including 40, as long as they develop relevant skills such as programming, statistics, and machine learning. Many professionals successfully transition into data science later in their careers by gaining certifications, building portfolios, and gaining practical experience.

What is the salary of a 2 year experience data scientist?

A data scientist with two years of experience typically earns between $70,000 and $100,000 annually, depending on the industry, location, and skill set. Proficiency in programming languages like Python or R and experience with machine learning tools can influence salary levels.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in machine learning, programming, and domain knowledge remain essential for designing and deploying AI solutions effectively.
What are popular job titles related to Computer Science Data Science jobs in Cambridge, MA? For Computer Science Data Science jobs in Cambridge, MA, the most frequently searched job titles are:
What job categories do people searching Computer Science Data Science jobs in Cambridge, MA look for? The top searched job categories for Computer Science Data Science jobs in Cambridge, MA are:
What cities near Cambridge, MA are hiring for Computer Science Data Science jobs? Cities near Cambridge, MA with the most Computer Science Data Science job openings:

Full-time

Medical, Retirement, PTO

Posted 20 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 264 frontline employees who took The Breakroom Quiz

14th of 138 rated financial services


Job description

Job Description:

Principal Data Scientist - Quantitative Decision Science & Advanced Analytics

Are you interested in operating as a senior scientific leader-owningtruth, rigor, and decision qualityfor complex business problems? FidelityInstitutional'sAI Center of Excellence (AI CoE) is seeking aPrincipal Data Scientistto serve as a highly tenured individual contributor and domain authority in data science, quantitative modeling, and advanced analytics.

This role isintentionally Data Science-first,with emphasis on hypothesisdriven analysis, statistical rigor, causal reasoning, and decision science. The Principal Data Scientist is accountable forwhat the model means, whether it is correct, and whether it should be trusted-not for building or operating production systems.

The Team

The Data Science function within the Fidelity Institutional AI CoE operates as the authority on measurement, experimentation, and quantitative decisionmaking. The team comprises senior data scientists, statisticians, and quantitative researchers who partner closely with platform, product, BI, and business teams, while maintaining clear ownership of scientific rigor, evaluation frameworks, and analytical truth.

As a Principal Data Scientist, you will operate as ascientific owner and mentor,influencing methodology, standards, and strategic direction across multiple initiatives.

Key Responsibilities

Advanced Data Science & Quantitative Modeling

  • Lead hypothesisdriven analyses to answer highimpact strategic and business questions

  • Design, develop, and evaluate statistical, econometric, and machine learning models where appropriate

  • Ensure models are theoretically sound, empirically validated, interpretable, and fitforpurpose

  • Review and challenge modeling approaches for bias, stability, assumptions, and misuse

Measurement, Evaluation & Decision Science

  • Define how success should be measured for complex analytics and AIenabled initiatives

  • Design robust evaluation frameworks including offline validation, backtesting, and live measurement

  • Ensure stakeholders can distinguish correlation from causation in analytical results

  • Elevate analytics from prediction accuracyto decision quality and business impact

Experimentation & Causal Inference

  • Design and review experiments including A/B tests, quasiexperiments, and observational studies

  • Apply causal inference techniques (e.g., uplift modeling,DiD, matched controls) to assess incrementality

  • Guide best practices for power analysis, inference, and result interpretation

  • Serve as a subjectmatter expert on "What worked, why, and by how much?"

Advanced Analytics Domains

  • Segmentation & Clustering:Design statistically grounded, interpretable segmentations with clear hypotheses and stability checks

  • Propensity, Likelihood & Uplift Modeling:Develop probabilistic and causal models to inform prioritization and intervention strategies

  • Recommendation & Prioritization Analytics:Guide recommendation logic rooted in statistics, behavioral science, and optimization-notblackboxML

  • Behavioral & Journey Analytics:Analyze longitudinal behavior patterns to identify drivers, frictions, and causal levers

  • Forecasting & Planning Analytics:Apply timeseries and probabilistic forecasting with uncertainty and scenario analysis

  • Large Language Models & Generative AI:Design, evaluate, and implement LLM-based solutions - including RAG pipelines, classification, and extraction tasks - with rigorous benchmarking, calibration analysis, hallucination measurement, and bias auditing to ensure outputs are explainable.

Scientific Leadership & Governance (NonManagerial)

  • Act as a senior reviewer and methodological authority across data science initiatives

  • Set informal standards for rigor, documentation, and reproducibility

  • Mentor senior and midlevel data scientists through technical guidance and peer review

Business Partnership & Influence

  • Translate complex quantitative results into clear, decisionoriented narratives for senior stakeholders

  • Challenge assumptions and narratives not supported by evidence

  • Influence strategy by grounding discussions in data, causality, and expected impact

Expertise and Skills You Bring

Education & Experience

  • Master's or PhD in Statistics, Economics, Mathematics, Operations Research, Computer Science, or related quantitative discipline

  • 10-14+ years of experience in data science, quantitative research, or advanced analytics

  • Proven track record of owning complex analytical problemsendtoend(from question formulation to decision impact)

Core Data Science & Scientific Expertise

  • Deep expertise in statistics, probability, and experimental design

  • Strong command of causal inference and incrementality measurement

  • Solid grounding in forecasting, optimization, and decision science

  • Demonstrated ability to assess modeling correctness, assumptions, and limitations

Technical Foundation

  • Advanced proficiency in Python for analysis and modeling (NumPy, Pandas, SciPy,Statsmodels, Scikitlearn)

  • Strong SQL skills and experience working with large analytical datasets (e.g.,Snowflake)

  • Handson proficiency with large language models and generative AI, including prompt design, retrievalaugmented generation, structured outputs, and agentic workflows, with demonstrated rigor in designing evaluations, defining taskspecific metrics, and applying statistical testing to assess reliability, calibration, hallucination risk, and incremental value over nongenerative approaches. Equally proficient in handson code development as well as the effective use of AIpowered coding assistants, applying both to accelerate analysis while maintaining correctness, reproducibility, and scientific rigor.

Ways of Working

  • Thinks like a scientist: hypothesisfirst, evidencedriven, and principled

  • High bar for rigor, interpretability, and defensibility of results

  • Comfortable challenging senior stakeholders using data and logic

  • Values clarity, elegance, and correctness over technical novelty

  • Operates as a trusted expert rather than a delivery engineer

How This Role Is Distinct

  • Senior Individual Contributor:Tenured individualcontributor role with broad organizational influence

  • Data Science-First:Focused on analytics, statistics, causality, and decision science

  • Strategic Impact:Owns critical analytical questions that shape business decisions and investments

The base salary range for this position is $126,000-255,000 USD per year.

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate's relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted.

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

Certifications:Category:Data Analytics and Insights

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