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Data Science Machine Learning Jobs in Boston, MA

Boseallaboutme

Sr. Data Scientist

Framingham, MA · 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 ...

Bose Corporation

Sr. Data Scientist

Framingham, MA · 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 ...

CarGurus

Senior Data Scientist

Boston, MA · On-site

... 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 ...

Roberts Recruiting

Senior Data Scientist

Boston, MA

The Data Scientist will analyze and model expected crop yield under various scenarios. Using large ... applied computer science, machine learning, mathematics, statistics, quantitative agronomy ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Design and implement complex data engineering processes to support innovative data science modeling

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All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Boston, MA

Data Science Machine Learning information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

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

As of May 29, 2026, the average yearly pay for data science machine learning in Boston, MA is $133,336.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,700.00 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, and why are they important?

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 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 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 are popular job titles related to Data Science Machine Learning jobs in Boston, MA? For Data Science Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Science Machine Learning jobs in Boston, MA look for? The top searched job categories for Data Science Machine Learning jobs in Boston, MA are:
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Boston, MA as of May 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 69% Physical, 5% Hybrid, and 26% Remote job distribution, with an average salary of $133,336 per year, or $64.1 per hour.

Senior Data Science and Machine Learning Engineer

1 point system

Bedford, MA • Remote

Contractor

Posted 28 days ago

Job description

Role

Senior Data Science and Machine Learning Engineer

Duration

6 months Contract to Hire

Location

Remote

Job Summary

    • We are seeking a Senior Data Science Engineer to design, build, and scale data-driven systems that power advanced analytics and machine learning across our organization. This role sits at the intersection of software engineering and data science; you’ll be responsible for building robust data pipelines, enabling experimentation, and deploying production-ready machine learning models.
    • As a senior team member, you will mentor junior engineers and data scientists, influence architectural decisions, and help shape the long-term AI and data strategy.

Key Responsibilities

    • Develop, deploy, and maintain machine learning models in production environments.
    • Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
    • Ensure high-quality data through monitoring, validation, and robust testing frameworks.
    • Architect and maintain data platforms and tools for experimentation, model serving, and feature engineering.
    • Explore and integrate Large Language Models (LLMs) and other generative AI approaches into business applications and data workflows.
    • Contribute to code reviews, technical design discussions, and best practices for the team.
    • Mentor and guide junior engineers/data scientists, fostering technical excellence and career growth.
    • Stay current with emerging technologies in Data Science, Machine Learning, LLM Ops, ML Ops.

Education Requirement

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • Master’s degree or PhD is a strong plus.

Experience

•            5+ years of experience in data engineering, machine learning engineering, or related roles.

•            Strong proficiency in Python (Pandas, NumPy, PySpark, or similar).

•            Solid understanding of ML model development, training, and deployment pipelines.

•            Experience with ML model monitoring and observability frameworks.

•            Experience with deep learning frameworks(TensorFlow, PyTorch).

•            Familiarity with CI/CD, version control (Git),and modern ML Ops practices.

Nice-to-Have

•            Contributions to open-source Data Science / Machine Learning libraries or frameworks.

•            Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization

Thanks and Regards

Monu Singh Chauhan | 1Point System LLC
Technical Recruiter  
monu.singh@1pointsys.com 

LinkedIn: linkedin.com/in/monu-singh-chauhan-610857204
115 Stone Village Drive • Suite C • Fort Mill, SC • 29708

         An E-Verified company | An Equal Opportunity Employer 

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