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Data Science Jobs in Massachusetts (NOW HIRING)

Merck & Co.

$194K - $305K/yr

The Translational Genome Analytics group within the Data, AI & Genome Sciences Department is recruiting a Director of Oncology Data Scientist to join our multi-modal biomarker discovery team. We are ...

Merck & Co.

$194K - $305K/yr

The Translational Genome Analytics group within the Data, AI & Genome Sciences Department is recruiting a Director of Oncology Biomarker Discovery to join an oncology data science team dedicated to ...

DraftKings

Data Science Manager, Marketing

Boston, MA · On-site

The Crown Is Yours As a Data Science Manager, you drive strategy and execution to power personalized experiences for millions of customers. You'll lead a team of data scientists and machine learning ...

Chubb

SVP, PRS - Data Science

Boston, MA · On-site

The successful candidate is a seasoned leader with expertise data science and model development and management. This position will be primarily responsible for personal lines product such as ...

Chubb

SVP, PRS - Data Science

Boston, MA · On-site

$249K - $333K/yr

The successful candidate is a seasoned leader with expertise data science and model development and management. This position will be primarily responsible for personal lines product such as ...

Biogen

Associate Director, AI/Data Science

Cambridge, MA · On-site

$176K - $242K/yr

This role will shape data science strategy, develop and evaluate AI/ML solutions, and partner across research & development leaders to transform how data is used to improve decision-making ...

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All JobsData Science JobsData Science Jobs in Massachusetts

Data Science information

See Massachusetts salary details

$41K

$134K

$214.6K

How much do data science jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data science in Massachusetts is $134,046.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,600.00 and $148,500.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Massachusetts? The most popular types of Data Science jobs in Massachusetts are:
What are popular job titles related to Data Science jobs in Massachusetts? For Data Science jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Massachusetts look for? The top searched job categories for Data Science jobs in Massachusetts are:
What cities in Massachusetts are hiring for Data Science jobs? Cities in Massachusetts with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Massachusetts as of August 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, 5% Hybrid, and 21% Remote job distribution, with an average salary of $134,046 per year, or $64.4 per hour.

Associate Director, Enterprise Data Science

Alkermes

Waltham, MA • On-site

$63K - $64K/yr

Full-time

Posted 11 days ago

Job description


Associate Director (Staff Data Scientist), Enterprise Data Science
Position Summary
As an Associate Director within the INDIGO | AI Innovation Lab, you will lead the development and scaling of data science capabilities across the enterprise while acting as a technical expert, thought partner, and mentor within the team. You will take ownership of key AI and machine learning initiatives to deliver data science-driven solutions that align with enterprise goals.
This is a hands-on role where you will develop and implement cutting- edge data science solutions, build and maintain digital products, and enable the democratization of data through scalable tools and best practices.
The ideal candidate will have a strong technical foundation in AI-driven Commercial Analytics within the pharmaceutical industry; inquisitive data science skills; clear and compelling communication skills; an exceptional sense of ownership and accountability; and demonstrated success delivering machine learning products that create business value.
This role is based in our Waltham location and would work a hybrid office schedule.
Responsibilities
Key Responsibilities
Support and Scale Data Science Use Cases
  • Develop and deploy complex analytical models and predictive insights to inform strategic decisions.

  • Implement data science solutions, including but not limited to predictive machine learning models, recommender systems, and agentic AI applications.

  • Lead development of commercial AI use cases including HCP targeting, customer suggestions, commercial opportunity identification, prescribing behavior prediction, and customer segmentation.

  • Scale proof-of-concept data science ideas and products into maintainable production software services; leverage best practices for production-ready code development and MLOps to build solutions that are stable, efficient, and scalable.

  • Partner with engineering teams to operationalize machine learning models and integrate outputs into business applications and digital workflows.

Stakeholder Engagement and Collaboration
  • Act as a key partner to cross-functional teams, providing technical and strategic guidance in the design, development, and implementation of AI-driven products and analytics solutions.

  • Serve as a trusted advisor to stakeholders by helping them understand INDIGO's capabilities and translate business challenges into high-impact data science opportunities.

  • Facilitate structured discovery and problem-framing sessions to identify opportunities where AI, machine learning, automation, and advanced analytics can drive measurable business value.

  • Collaborate closely with commercial business leaders and domain experts to ensure models and solutions reflect real-world business processes and market dynamics.

  • Influence decision-making through clear, actionable communication, synthesizing complex analytical results into insights that resonate with both technical and non-technical audiences.

  • Champion change management and user adoption, ensuring stakeholders understand, trust, and effectively integrate AI-driven recommendations into their workflows.

  • Build long-term partnerships with business owners, fostering ongoing collaboration, feedback loops, and continuous improvement for products and models in production.

Lead the Development of Data Science Capabilities
  • Design and build production-grade digital products, reusable frameworks, and scalable AI/ML platforms that drive commercial performance and establish consistent foundations for future AI applications.

  • Lead and manage high-impact data science initiatives across the organization, including scope, timelines, risks, and resource planning.

  • Drive the development of scalable machine learning capabilities that can support multiple brands and commercial use cases through reusable frameworks and automation.

  • Evangelize and contribute to scaled adoption of AI and machine learning capabilities across the organization.

  • Stay updated with advancements in data science, machine learning, and generative AI and evaluate emerging technologies for practical business application.

  • Track and communicate progress on data science initiatives while managing shifting priorities and business needs.

  • Champion FAIR principles and guide the organization in their application to ensure long-term data usability and accessibility.

Functional Ownership of Digital Products
  • Bring an end-to-end product lifecycle management mindset to INDIGO initiatives, with a clear focus on maximizing long-term business value.

  • Take ownership of Commercial AI and analytics products, ensuring reliability, scalability, business relevance, and ongoing stakeholder adoption.

  • Play a key role in shaping product and portfolio strategy by contributing expert judgment and nuanced thinking on the direction, growth, and integration of the products they own.

  • Mentor and develop the talent supporting their product portfolio, fostering a collaborative and continuously learning team environment.

Qualifications
Qualifications
Basic Qualifications
Education
  • Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Economics, Engineering, or a related quantitative field. Ph.D. preferred

Experience
  • 10+ years building and deploying advanced analytics, machine learning, and AI solutions that deliver measurable business impact.

  • Experience supporting Commercial Analytics use cases within pharmaceutical, biotechnology, or healthcare organizations strongly preferred.

  • Experience leading cross-functional AI and data science initiatives from problem framing through deployment and value realization.

  • Experience managing stakeholder relationships and influencing business decision-making at multiple organizational levels.

Technical Skills
  • Proficiency in production programming using Python and SQL.

  • Deep understanding of machine learning algorithms, statistical analysis techniques, predictive modeling methodologies, and end-to-end MLOps management.

  • Familiarity with cloud computing and ML platforms; AWS experience required and Snowflake experience preferred. Prior experience with use of AI tools in code development and management workflows is a plus.

  • Experience with data engineering, feature engineering, data governance, and scalable machine learning pipelines (dbt experience preferred).

  • Experience working with commercial data assets such as CRM, prescribing, claims, specialty pharmacy, patient services, or engagement data preferred.

Core Competencies
  • Proven ability to design and implement end-to-end AI and machine learning solutions from business problem definition through value realization.

  • Strong business acumen with the ability to connect technical solutions to commercial outcomes.

  • Strong problem-solving and analytical skills, with an aptitude for both technical innovation and stakeholder management.

  • Strong leadership and project management skills, with experience mentoring and developing technical talent.

  • Excellent communication and interpersonal skills with the ability to collaborate effectively across cross-functional teams and executive stakeholders.

  • Strong organizational skills, with demonstrated ability to manage multiple projects and competing priorities and ambiguities in a fast-paced environment.

  • Strong ownership mindset and accountability for outcomes.

Preferred Qualifications
  • Experience in pharmaceutical, biotechnology, or healthcare industries.

  • Direct experience supporting Commercial, Sales, Marketing, Market Access, Patient Services, or Field Force effectiveness initiatives.

  • Familiarity with Veeva CRM, IQVIA, claims, prescription, specialty pharmacy, and patient-level commercial datasets.

  • Familiarity with regulatory and compliance standards applicable to healthcare data (e.g., HIPAA).

  • Exposure to GenAI innovation, agentic AI systems, and advanced customer intelligence platforms.

The annual base salary for this position ranges from $160,000 to $180,000. In addition, this position is eligible for an annual performance pay bonus. Exact compensation may vary based on skills, training, knowledge, and experience. Alkermes offers a competitive benefits package. Additional details can be found on our careers website: www.alkermes.com/careers#working-here
Alkermes has recently adopted a hybrid working environment to support and meet the needs of employees and this role will operate in a flexible environment with 60% of time in the office and 40% from home. This position is eligible for the hybrid workplace model, requiring work to be completed onsite at our Waltham, MA office at least 3 days per week. This role is not eligible for fully remote work.
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About Us
Why join Team Alkermes?
Alkermes applies its decades of deep neuroscience expertise to develop medicines designed to help people living with complex and difficult-to-treat psychiatric and neurological disorders. A global biopharmaceutical company, headquartered in Ireland with U.S. locations in Massachusetts and Ohio, we seek to make a meaningful difference in the way people manage their diseases. We have a portfolio of proprietary commercial products for the treatment of alcohol dependence, opioid dependence, schizophrenia, bipolar I disorder and narcolepsy, and a pipeline of clinical and preclinical candidates in development for various psychiatric and neurological disorders.
We are proud to have been recognized as an employer of choice by many national organizations. In 2024 and 2025, we were certified as a Great Place to Work in the U.S. and named one of Massachusetts' Top Places to Work by the Boston Globe, a Best Place to Work in Greater Cincinnati by the Cincinnati Business Courier and recognized as a Best Place to Work in BioPharma by Fortune Magazine.
Alkermes, Inc. is an equal employment opportunity employer and does not discriminate against any qualified applicant or employee because of race, creed, color, age, national origin, ancestry, religion, gender, sexual orientation, gender expression and identity, disability, genetic information, veteran status, military status, application for military service or any other characteristic protected by local, state or federal law. Alkermes also complies with all work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Alkermes is an E-Verify employer.

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