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Data Science Machine Learning Jobs in Massachusetts

Sr. Data Scientist

Framingham, MA ยท On-site

$120K - $165K/yr

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Sr. Data Scientist

Framingham, MA ยท On-site

$120 - $165/hr

Your mission will be to develop worldโ€‘class AI, data science, machine learning, and related solutions that tackle our biggest challenges, focusing on the strategy for and building the next ...

Experience. 10+ years of professional experience in data science, machine learning, or AI, including 5+ years working on AI/ML or GenAI solutions. Proven track record of developing, deploying, and ...

New

... Data Science team with a focus on CarGurus's international products, the Senior Data Scientist, International will be responsible for implementing, training and testing machine learning models in ...

You'll lead a team of data scientists and machine learning engineers, guiding projects from concept through production and delivering scalable, high-performing machine learning systems. In this role ...

AI Data Science Expert - Remote

Boston, MA ยท Remote

$100 - $200/hr

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

AI Data Science Expert - Remote

Boston, MA ยท Remote

$100 - $200/hr

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Posted today

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Data Science Machine Learning information

See Massachusetts salary details

$41K

$134K

$214.6K

How much do data science machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data science machine learning 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 are the key skills and qualifications needed to thrive as a data science machine learning professional?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a data science machine learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.
What cities in Massachusetts are hiring for Data Science Machine Learning jobs? Cities in Massachusetts with the most Data Science Machine Learning job openings:
Infographic showing various Data Science Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $134,046 per year, or $64.4 per hour.

Other

Posted 9 days ago


Job description


Join a cutting-edge AI Platform team as a Senior Data Scientist in a 6-month remote contract-to-hire opportunity. You'll help develop enterprise-scale AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, NLP, machine learning, and distributed AI architectures to support complex research, document intelligence, and workflow automation systems.
This role offers the opportunity to work on some of the most advanced AI challenges in industry today. The team is building next-generation intelligent systems that combine LLMs, retrieval technologies, and autonomous agents to solve highly complex information and decision-making problems. They're looking for someone who can drive innovation, shape AI strategy, and help bring cutting-edge research into production.
Contract Duration: 6 Months (Contract-to-Hire)
Required Skills & Experience
Bachelor's degree required; Master's degree preferred
5-8+ years of experience in Data Science, Machine Learning, or Applied AI
Strong experience with Large Language Models (LLMs) and Generative AI applications
Hands-on experience designing and deploying RAG systems
Expertise in machine learning, NLP, and information retrieval techniques
Experience building and deploying production AI/ML systems
Strong Python programming skills
Experience working with distributed systems and cloud-based AI environments
Understanding of agentic AI architectures and autonomous workflows
Strong analytical, communication, and problem-solving skills
Desired Skills & Experience
Experience building enterprise-scale AI platforms
Familiarity with vector databases and semantic search technologies
Knowledge of legal, regulatory, or document-intensive data environments
Experience with model evaluation, monitoring, and optimization
Exposure to workflow automation and intelligent agent frameworks
Experience collaborating across data science, engineering, and product teams
Advanced degree in Data Science, Computer Science, Machine Learning, or a related field
What You Will Be Doing
Tech Breakdown
40% LLMs, RAG, and Generative AI
30% Machine Learning & NLP
20% Agentic AI & Intelligent Automation
10% Distributed Systems & Platform Collaboration
Daily Responsibilities
75% Hands On
5% Management Duties
20% Team Collaboration