1

Amazon Data Science Jobs in Massachusetts (NOW HIRING)

Agentic AI, AI & Data Science Engineer

Boston, MA · On-site

$124K - $149K/yr

Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be ... Amazon Bedrock (foundation models, model evaluation, and agent orchestration); Knowledge bases ...

$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 ...

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

next page

Showing results 1-20

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 Jul 30, 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 hire data scientists?

Yes, Amazon hires data scientists to analyze large datasets, develop machine learning models, and support business decision-making. Candidates typically need strong skills in statistics, programming, and tools like Python or R, along with relevant experience or education in data science or related fields.

Can data scientists make $300k?

Data scientists at companies like Amazon can potentially earn $300,000 or more annually, especially with seniority, extensive experience, advanced skills in machine learning, and in high-cost-of-living areas. Compensation often includes base salary, bonuses, and stock options, which can significantly increase total earnings.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including at 40 or older. Success in data science depends on skills, experience, and continuous learning, such as mastering programming languages like Python or R and understanding machine learning concepts. Many professionals transition into data science later in their careers and find opportunities based on their expertise and problem-solving abilities.

What is an Amazon Data Science job?

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.

How much does a Data Scientist make at Amazon?

The average salary for a Data Scientist at Amazon is around $120,000 to $150,000 per year, depending on experience, location, and level. Compensation may also include bonuses, stock options, and benefits, with more senior roles earning higher salaries. Skills in machine learning, data analysis, and proficiency with tools like Python and SQL are often 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:
Infographic showing various Amazon Data Science job openings in Massachusetts as of July 2026, with employment types broken down into 1% Locum Tenens, 90% Full Time, 6% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $180,220 per year, or $86.6 per hour.

Principal Scientist, Data Science (Data Products, Integration & Analysis)

Johnson & Johnson

Cambridge, MA

Full-time

Retirement, PTO

Posted 13 days ago


Johnson & Johnson rating

8.2

Company rating: 8.2 out of 10

Based on 110 frontline employees who took The Breakroom Quiz

31st of 86 rated pharmaceutical


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Horsham, Pennsylvania, United States of America, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

Position Summary

The Principal Scientific Data Scientist will lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.

This individual will be responsible for creating scalable, interoperable, and AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence domains, and enable the creation of validated-biomarker data assets . The role will establish the data architecture, integration strategy, metadata framework, and productization approach needed to support semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications.

Working closely with scientific stakeholders, knowledge architects, AI engineers, and Amazon BioDiscovery platform teams, this individual will define the future-state scientific data ecosystem and ensure high-quality data products are delivered to support translational science and patient safety initiatives.

Build AI reasoning models to support data-driven translational safety decision making.

Mission

Build and operationalize AI-ready scientific data products that enable seamless integration, harmonization, and reuse of data across the drug discovery and development lifecycle.

Key Responsibilities

Scientific Data Product Strategy

Define and execute a scientific data product strategy supporting:

  • Discovery Research

  • Translational Science

  • Preclinical Safety

  • Clinical Development

  • Pharmacovigilance

  • Real-World Evidence

  • Establish reusable, scalable data products that support analytics, AI, knowledge graph, and scientific reasoning use cases.

  • Develop product roadmaps aligned with organizational priorities and scientific objectives.

Data Integration Architecture

  • Design integration frameworks connecting heterogeneous scientific data sources.

  • Define data harmonization strategies spanning:

    • SEND

    • SDTM

    • ADaM

    • MedDRA

    • Imaging

    • Omics

    • Biomarker

    • Pathology

    • Real-world data

  • Create architecture patterns supporting cross-domain data interoperability.

Digital Platform Leadership

  • Define the implementation strategy for scientific data products deployed on AWS

  • Partner with Amazon engineering and deployed platform resources to deliver scalable data pipelines and data products.

  • Provide technical leadership and architectural oversight for implementation activities aligned recommendations from the Data Strategy group.

  • Ensure digital solutions align with enterprise architecture, security, governance, and AI-readiness requirements.

Data Product Development

  • In collaboration with Data Strategy group, lead design and implementation of:

    • Curated datasets

    • Semantic-ready data products

    • Feature stores

    • Metadata products

    • Scientific data services

    • AI-ready data assets

  • Establish reusable patterns for data onboarding, transformation, validation, and publication.

Data Quality & Metadata

  • Define metadata standards and data quality frameworks.

  • Implement lineage, provenance, traceability, and FAIR data principles.

  • Establish monitoring and quality controls for scientific data products.

Data Analysis:

  • Build predictive AIML models to support translational safety decision making.

Stakeholder Engagement

  • Partner with:

    • Discovery Scientists

    • Toxicologists

    • Clinical Scientists

    • Safety Scientists

    • Data Scientists and Data Strategy business partners.

    • Knowledge Architects

    • AI Engineers

  • Translate scientific questions into scalable data products and technical solutions.

Required Qualifications

Education

  • Master's or PhD in:

    • Computer Science

    • Data Engineering

    • Bioinformatics

    • Biomedical Informatics

    • Information Systems

    • Computational Biology

    • Related scientific discipline

Experience

  • 5+ years of experience in scientific data engineering, data architecture, data products, or life sciences informatics.

  • Demonstrated experience designing and delivering enterprise-scale scientific data products.

  • Experience supporting drug discovery, development, clinical research, or pharmacovigilance organizations.

  • Experience developing predictive models in drug discovery, development, clinical research, or pharmacovigilance organizations.

Technical Expertise

Strong expertise in:

  • Data architecture

  • Data modeling

  • Data product design

  • Cloud-native data platforms

  • Metadata management

  • Data governance

  • Predictive model development

Experience with:

  • AWS-based data platforms

  • Data lakes and lakehouses

  • Distributed data processing

  • APIs and data services

  • Data cataloging and lineage solutions

Scientific Data Standards

Strong familiarity with:

  • SEND

  • SDTM

  • ADaM

  • MedDRA

Preferred familiarity with:

  • FHIR

  • OMOP

  • DICOM

  • Biomarker and omics data standards

Preferred Qualifications

  • Experience supporting knowledge graphs, semantic architectures, or GraphRAG initiatives.

  • Experience building AI-ready data products and feature stores.

  • Familiarity with ontology-driven data integration approaches.

  • Experience partnering with cloud providers or external platform teams.

  • Experience operating in highly regulated scientific environments.

Leadership Competencies

  • Strategic thinker capable of defining long-term data product roadmaps.

  • Strong communicator who can bridge scientific and technical communities.

  • Ability to influence cross-functional teams without direct authority.

  • Strong execution focus with a bias toward scalable, reusable solutions.

  • Passion for transforming biomedical R&D through data, AI, and modern engineering practices.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or contact AskGS to be directed to your accommodation resource.

#LI-GR1

#LI-Hybrid

#JRDDS

#JNJDataScience

#JRD

Required Skills:

Preferred Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

The anticipated base pay range for this position is :

$117,000.00 - $201,250.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).
This position is eligible to participate in the Company's long-term incentive program.
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits

What Johnson & Johnson employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom