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Data Science Jobs in Massachusetts (NOW HIRING)

Kemper

Data Science Manager

Boston, MA · Hybrid

Manages a small team of data scientists and data engineers to research, design, develop, deploy, and maintain machine learning, AI, and agentic AI solutions supporting the Claims organization.

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 ...

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · On-site

$34.44/hr

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · Remote

$100 - $200/hr

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

YO AI Labs

AI Data Science Expert - Remote

Boston, MA · Remote

$100 - $200/hr

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

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 ...

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See Massachusetts salary details

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$134K

$214.6K

How much do data science jobs pay per year?

As of Aug 21, 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.

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 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.

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 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.

Is a data scientist in high demand?

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 jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
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 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $134,046 per year, or $64.4 per hour.

Data Science Manager

Kemper

Boston, MA • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday

Job description

Location(s)

Alpharetta, Georgia, Bloomington, Illinois, Boston, Massachusetts, Chicago, Illinois, Columbus, Ohio, Hartford, Connecticut, Omaha, Nebraska

Details

Kemper is one of the nation's leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture, valuable opportunities for personal development and professional challenge, and a healthy work-life balance can be highly motivating and productive. Kemper's products and services are making a real difference to our customers, who have unique and evolving needs. By joining our team, you are helping to provide experience to our stakeholders that delivers on our promises.

Position Summary:

Responsible for developing and delivering machine learning and AI solutions for Claims use cases, including claim triage, fraud detection, severity prediction, litigation, subrogation, workflow optimization, and other claims analytics applications, while providing technical leadership and leading projects. This role includes direct people leadership responsibilities, including coaching, mentorship, and performance management

Position Responsibilities:

  • Manages a small team of data scientists and data engineers to research, design, develop, deploy, and maintain machine learning, AI, and agentic AI solutions supporting the Claims organization.
  • Communicates project progress, insights, results, and recommendations to business partners and senior leadership.
  • Manages project scope, expectations, and timelines.
  • Collaborates with Data Engineering, IT, and business partners to operationalize machine learning and AI solutions.
  • Follows the model governance process including planning, documentation, validation, deployment, monitoring, and review.
  • Oversees model performance and supports ongoing monitoring and continuous improvement of deployed solutions.
  • Develops and mentors team members to maintain technical excellence in AI/ML, software engineering, and solution design.

Position Qualifications:

  • Graduate degree in Mathematics, Statistics, Engineering, or other STEM field with 6-8 years of experience in insurance industry or related industry in a data science/analytics environment.
  • PhD in Mathematics, Statistics, Engineering, or other STEM fields preferred with 4-6 years of experience in insurance industry or related industry in a data science, analytics, or AI environment.
  • Prior experience mentoring or managing talent.
  • Experience developing and deploying predictive models into production.
  • At least 6 years of experience with statistical modeling, machine learning, and AI technologies.
  • Strong proficiency in Python and SQL.
  • Experience with software development best practices, including version control (Git), code reviews, testing, and model lifecycle management.
  • Strong written and verbal communication skills, including the ability to communicate technical concepts and analytical insights to business stakeholders and senior leadership.
  • Claims experience preferred.
  • This position can be worked hybrid out of a local Kemper office. Remote options will be considered for non-local candidates.
  • Sponsorship is not accepted for this opportunity
  • The range for this position is $115,700 to $192,900. When determining candidate offers, we consider experience, skills, education, certifications, and geographic location among other factors. This job is eligible for an annual discretionary bonus and Kemper benefits (Medical, Dental, Vision, PTO, 401k, etc.)

Kemper is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other status protected by the laws or regulations in the locations where we operate. We are committed to supporting diversity and equality across our organization and we work diligently to maintain a workplace free from discrimination.

Kemper does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Kemper and Kemper will not be obligated to pay a placement fee.
Kemper will never request personal information, such as your social security number or banking information, via text or email. Additionally, Kemper does not use external messaging applications like WireApp or Skype to communicate with candidates. If you receive such a message, delete it.

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