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Data Science Research Jobs in Boston, MA (NOW HIRING)

Newton Research

Data Scientist

Boston, MA · On-site

$160K - $180K/yr

Data Scientist Company Description Newton Research is a fast-growing software start-up founded by repeat entrepreneurs and well-funded by blue chip venture capital firms. We are building the next ...

Jj

Principal Scientist Data Science

Cambridge, MA

Data Science Job Category: Scientific/Technology All Job Posting Locations: Barcelona, Spain ... Research and development areas encompass oncology, cardiovascular and metabolic disorders ...

Novartis

Associate Director, Data Science

Cambridge, MA · Hybrid

$160K - $297K/yr

This role reports to the Head of Data Science in the PKS M&S team within Translational Medicine in Biomedical Research. Key responsibilities: * Shape and advance AI-driven MIDD by integrating ...

Moderna Therapeutics

Data Scientist

Cambridge, MA · On-site +1

$121K - $194K/yr

... Science and Artificial Intelligence (DSAI)Researchteam.This role will support and execute on ... Support and execute on research projects that leverageinternal and external assay datato impact ...

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Showing results 21-40

All JobsData Science Research JobsData Science Research Jobs in Boston, MA

Data Science Research information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do data science research jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data science research in Boston, MA is $133,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,800.00 per year, depending on experience, location, and employer.

What is data science research?

Data science research involves using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Researchers in this field work on developing new data analysis techniques, machine learning models, and data-driven solutions to solve complex problems. The work often includes designing experiments, analyzing large datasets, and publishing findings to advance the understanding of data science methodologies.

How does a data science researcher typically collaborate with other departments within an organization?

Data Science Researchers frequently work cross-functionally, collaborating with teams such as engineering, product management, and business analytics. They often translate complex research findings into actionable insights, guiding product development or business strategies. Regular meetings, joint project planning, and code reviews are common, ensuring that research outcomes align with organizational goals. Effective communication and teamwork are key to integrating advanced data solutions into real-world applications.

What are the key skills and qualifications needed to thrive as a data science researcher, and why are they important?

To thrive as a Data Science Researcher, you need strong analytical skills, expertise in statistics and machine learning, and an advanced degree in a quantitative field such as computer science, mathematics, or engineering. Proficiency with programming languages like Python or R, data visualization tools, and experience using platforms such as TensorFlow or PyTorch is typically required. Curiosity, creativity, and clear communication are essential soft skills for designing research questions, interpreting results, and sharing findings with diverse audiences. These skills and qualities are crucial for driving innovative solutions and impactful insights in data-driven environments.

What is the difference between Data Science Research vs Data Analyst?

AspectData Science ResearchData Analyst
CredentialsTypically requires advanced degrees (Master's or PhD) in Data Science, Statistics, or related fieldsOften requires a Bachelor's or Master's degree in Data Analysis, Statistics, or related areas
Work EnvironmentResearch labs, academic institutions, or R&D departments within companiesBusiness environments, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutions, tech companies focusing on innovationRetail, finance, healthcare, and other industries focusing on data-driven decision making

Data Science Research focuses on developing new algorithms, models, and theories, often in academic or R&D settings. In contrast, Data Analysts primarily interpret existing data to generate reports and insights for business decisions. Both roles require strong analytical skills but differ in scope, goals, and work environment.

What do data science researchers do?

Data science researchers analyze large datasets to identify patterns, develop models, and generate insights that inform decision-making. They often use programming languages like Python or R, and tools such as machine learning algorithms and statistical methods. Their work typically involves experimentation, data cleaning, and collaboration with other teams to solve complex problems.

What are popular job titles related to Data Science Research jobs in Boston, MA?

For Data Science Research jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Data Science Research jobs in Boston, MA look for?

The top searched job categories for Data Science Research jobs in Boston, MA are:

Data Science Research jobs near you
Infographic showing various Data Science Research job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $133,343 per year, or $64.1 per hour.

Principal Scientist Data Science

Socket.dev

Cambridge, MA • On-site

$117 - $201/hr

Other

Posted 9 days ago

Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Barcelona, Spain, Cambridge, Massachusetts, United States of America, Hyderabad, Andhra Pradesh, India, Madrid, Spain, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Scientist. The ideal candidate will leverage, adapt, and extend machine learning (ML), optimization techniques, and GenAI techniques to create computational pipelines supporting global clinical operations including enrollment forecasting, cost estimation and optimization, and country/site selection.

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine

Key responsibilities:
  • Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions to support clinical trial operations.
  • Leverage operational, RWD, and cost data to build ML predictive models and optimization engines to 1) predict outcomes of interest, 2) highlight tradeoffs between competing objectives, 3) recommend optimal operational scenarios, and 4) generate actionable insights, enabling early intervention and risk management.
  • Adapt large language models (LLMs) for tailored information extraction and to create solutions including
    • conducting comparative analytics on clinical trial protocols and trial similarity assessment,
    • clinical trial data harmonization and standardization,
    • schedule of activity optimization, and
    • eligibility criteria evaluation,
  • Stochastic enrollment simulations to forecast operational and patient journey outcomes including enrollment and study completion.
  • Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.
  • Coaches and trains junior colleagues in techniques, processes, and responsibilities.
Required qualifications:
  • A Ph.D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar),
  • 5+ years of industry experience delivering on data science projects using ML predictive modeling, multi-objective optimization, natural language processing, and GenAI.
  • Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting.
  • Experience building multi-objective optimization engines to navigate complex trade-offs using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming.
  • Experience with GenAI and clinical LLMs for document parsing and clinical concept disambiguation and harmonization.
  • Proficient in MLOps practices and tools (MLflow, Kedro); Git usage, CI/CD stacks (Jenkins, GitLab) DevOps tools.
  • Proficiency with programming languages Python and SQL,
  • Experience with python LLM tools (e.g., DSPy, LangChain), optimization tools (e.g., pymoo) and ML tools (e.g., Scikit-learn, XGBoost, Optuna, PyMc),
  • Demonstrated experience and familiarity with clinical operational data, real world data, electronic health records and claims, and financial data.
Preferred qualifications:
  • Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries.
  • Hand-on experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC and/or EHR to build ML models for estimating operational outcomes or RWE outcomes.
Required Skills: Preferred Skills:
  • Advanced Analytics
  • Coaching
  • Critical Thinking
  • Data Analysis
  • Data Privacy Standards
  • Data Quality
  • Data Reporting
  • Data Savvy
  • Data Science
  • Data Visualization
  • Digital Fluency
  • Econometric Models
  • Organizing
  • Process Improvements
  • Strategic Thinking
  • Technical Credibility
  • Workflow Analysis
The anticipated base pay range for this position is :

$117,000.00 - $201,250.00

Additional Description for Pay Transparency:
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