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Amazon Data Science Jobs in Massachusetts (NOW HIRING)

Jobtailor

Lead Data Scientist

Boston, MA · On-site

$120 - $190/hr

* Design, build, and deploy autonomous AI agents using frameworks like Amazon Bedrock and AgentCore ... Translate complex data science and statistical concepts into clear recommendations, stories, and ...

Merck & Co.

$64K - $65K/yr

Amazon Web Services (AWS), Bioinformatics, Biostatistics, Computer Science, CRISPR-Cas System, Data Engineering, Data Modeling, Data Science, Data Visualization, Genome, Genomics, Hypothesis Testing ...

Jj

Principal Data Scientist - Oncology

Cambridge, MA · On-site

Data Science Job Category: Scientific/Technology All Job Posting Locations: Cambridge ... SPARQL, RDF, OWL), familiarity with graph databases (Neo4j, Amazon Neptune). * Proven work with ...

Xometry

Senior Data Scientist, Costing

Waltham, MA · Hybrid

Use data science and machine learning principles to develop effective predictive models * Write ... Use cloud resources (e.g., Amazon Web Services) to prepare and process data * Query and extract ...

Xometry

Senior Data Scientist, Costing

Waltham, MA · On-site

Use data science and machine learning principles to develop effective predictive models * Write ... Use cloud resources (e.g., Amazon Web Services) to prepare and process data * Query and extract ...

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All JobsAmazon Data Science JobsAmazon Data Science Jobs in Massachusetts

Amazon Data Science information

See Massachusetts salary details

$50.2K

$180.2K

$265.9K

How much do amazon data science jobs pay per year?

As of Aug 10, 2026, the average yearly pay for amazon data science in Massachusetts is $180,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,800.00 and $185,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Amazon data science position, and why are they important?

To thrive as an Amazon Data Science professional, you need strong analytical abilities, expertise in statistics and machine learning, and a solid educational background in computer science, mathematics, or a related field. Proficiency in programming languages such as Python or R, familiarity with big data tools like AWS, Spark, or Hadoop, and relevant certifications (e.g., AWS Certified Data Analytics) are often required. Effective communication, business acumen, and collaborative problem-solving set exceptional candidates apart. These skills are crucial for transforming complex data into actionable insights that drive impactful business decisions at Amazon.

What types of projects and challenges can I expect as an Amazon data science team member?

As an Amazon Data Science team member, you can expect to work on projects ranging from optimizing supply chains and recommendation systems to improving customer experiences and forecasting demand. Daily responsibilities often involve analyzing large data sets, building predictive models, and collaborating closely with product managers, software engineers, and business leaders. The pace is fast, with opportunities to tackle complex problems that have a direct impact on Amazon’s customers and operations. You’ll also have the chance to grow your skills through cross-team projects, participation in internal workshops, and exposure to emerging data science technologies.

Does Amazon have data science jobs?

Yes, Amazon offers data science jobs across various teams, focusing on areas such as machine learning, data analysis, and predictive modeling. These roles typically require skills in programming, statistics, and tools like Python, R, or SQL, and often involve working in collaborative, fast-paced environments. Candidates should review Amazon's careers page for current openings and specific role requirements.

What is an Amazon data science?

An Amazon Data Science job involves leveraging data to drive business decisions, optimize operations, and enhance customer experiences. Data scientists at Amazon work with machine learning, statistical modeling, and big data technologies to analyze vast datasets and generate actionable insights. They collaborate with engineering, product, and business teams to develop data-driven solutions for challenges such as recommendation systems, demand forecasting, and fraud detection. Strong programming skills in Python or Scala, expertise in SQL, and experience with AWS tools are commonly required.

What are the most commonly searched types of Amazon Data Science jobs in Massachusetts? The most popular types of Amazon Data Science jobs in Massachusetts are:
Amazon Data Science jobs near you
Infographic showing various Amazon Data Science job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $180,220 per year, or $86.6 per hour.

Lead Data Scientist

Jobtailor

Boston, MA • On-site

$120 - $190/hr

Other

Posted 5 days ago

Job description

  • Design, build, and deploy autonomous AI agents using frameworks like Amazon Bedrock and AgentCore to solve business problems in pricing, sales, operations, and customer interactions.
  • Apply machine vision and feature extraction on home attributes (photos, plans, finishes) to inform premium pricing and personalization strategies.
  • Engineer and maintain data pipelines and systems supporting all models and agents, ensuring scalability and reliability.
  • Integrate agents with enterprise systems and protocols (MCP servers, A2A protocol, internal APIs).
  • Design and run experiments (A/B tests, multi-armed bandits, uplift models) to measure and optimize model and agent performance.
  • Ensure observability and reliability of deployed agents, including logging, evaluation, monitoring, and drift detection.
  • Proactively gather feedback from stakeholders and adapt solutions for adoption and measurable impact.
  • Translate complex data science and statistical concepts into clear recommendations, stories, and visualizations for executives and non-technical audiences.
  • Favor incremental, explainable solutions that deliver quick wins and scale over time.
  • Drive experimentation with new tools and approaches, ensuring robustness, governance, and scalability in production deployments.
  • Share learnings with the broader team to raise the bar on data science and agentic development across the organization.
  • Manage timelines and expectations transparently with both the data science team and business stakeholders.
Requirements
  • Bachelor’s or Master’s degree in Statistics, Economics, Math, Computer Science, Data Science, Machine Learning, or related field (or equivalent experience)
  • 5+ years of relevant experience (1+ with PhD, 3+ with MS) as a data scientist, ML engineer, or applied AI developer delivering production-ready models and systems
  • Strong proficiency in Python and SQL
  • Hands‑on experience with AI development frameworks (LangChain, Strands, Amazon Bedrock, AgentCore, or equivalent)
  • Experience with experimentation frameworks (A/B testing, uplift modeling, multi‑armed bandits, causal ML)
  • Exposure to machine vision techniques (CNNs, transfer learning, embeddings) and NLP techniques (embeddings, transformers, prompt engineering)
  • Understanding AI agent observability (evaluation frameworks like LangFuse, RAGAS, Weights & Biases, custom monitoring)
  • Experience with system integrations: APIs, A2A protocol, MCP servers, orchestration pipelines
  • Strong engineering skills: ability to design and maintain production pipelines, microservices, and scalable systems
  • Proven ability to navigate ambiguity, rapidly prototype, and move solutions into production
  • Collaborative communicator who can align technical solutions with business priorities across diverse stakeholders
Hard Skills
  • Python
  • SQL
  • machine vision
  • feature extraction
  • A/B testing
  • multi-armed bandits
  • uplift modeling
  • data pipelines
  • AI development frameworks
  • NLP techniques
Soft Skills
  • collaborative communication
  • navigating ambiguity
  • prototyping
  • stakeholder alignment
  • translating complex concepts
  • feedback gathering
  • adaptability
  • problem-solving
  • organizational skills
  • transparency
Certifications & Qualifications
  • Bachelor’s degree
  • Master’s degree
  • PhD
  • Data Science certification
  • Machine Learning certification
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