ZipRecruiter

Log In

1

Chemistry Data Science Jobs (NOW HIRING)

Pfizer

Senior Computational Chemist

La Jolla, CA · On-site +1

$106K - $176K/yr

MLCS supports medicinal chemistry and drug design teams by enabling data-driven decision making, scalable cheminformatics platforms, and impactful scientific applications across the discovery ...

Pfizer, Inc.

Senior Computational Chemist

La Jolla, CA · On-site

$106K - $176K/yr

MLCS supports medicinal chemistry and drug design teams by enabling data-driven decision making, scalable cheminformatics platforms, and impactful scientific applications across the discovery ...

MSD

Senior Specialist, Data Science

San Francisco, CA

$129K - $203K/yr

D. or M.S. in Computer Science, Computational Biology, Computational Chemistry, Bioinformatics ... Computational Biology, Computational Chemistry, Data Engineering, Data Modeling, Data Science, Data ...

MSD

Senior Specialist, Data Science

West Point, PA

$129K - $203K/yr

D. or M.S. in Computer Science, Computational Biology, Computational Chemistry, Bioinformatics ... Computational Biology, Computational Chemistry, Data Engineering, Data Modeling, Data Science, Data ...

Novartis

Director Oncology Data Science LMW

Cambridge, MA · On-site

$194K - $361K/yr

Collaborate closely with the Oncology Data Science AI team and other teams such as generative chemistry teams on the development and implementation of innovative machine learning algorithms, AI ...

next page

Showing results 1-20

All JobsChemistry Data Science Jobs

Chemistry Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do chemistry data science jobs pay per year?

As of Jul 2, 2026, the average yearly pay for chemistry data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

Is 30 too late for data science?

For a Chemistry Data Science role, starting a career at 30 is not too late. Many professionals transition into data science later in life, and acquiring relevant skills such as programming, statistics, and domain knowledge can be done through online courses or certifications. Age is less important than skills, experience, and continuous learning in this field.

What careers can I get with a data science degree?

A data science degree can lead to careers such as data scientist, data analyst, machine learning engineer, or research scientist. These roles involve analyzing large datasets, developing models, and using tools like Python, R, or SQL. They are common in industries like healthcare, finance, technology, and pharmaceuticals, often requiring strong statistical and programming skills.

What are some typical responsibilities of a Chemistry Data Science professional in an industrial or research setting?

Chemistry Data Science professionals are often tasked with analyzing large datasets derived from laboratory experiments or chemical manufacturing processes to uncover patterns, improve yields, or predict properties of new compounds. On a day-to-day basis, they may design predictive models, collaborate with chemists and engineers, and use advanced software to manage and interpret chemical data. The role frequently involves presenting findings to cross-functional teams and supporting decision-making through evidence-based recommendations. This collaborative approach helps drive innovation and efficiency in product development, quality control, or scientific research projects.

Can a chemist be a data scientist?

Yes, a chemist can become a data scientist by developing skills in programming, statistics, and machine learning, often using tools like Python or R. Their background in chemistry provides domain expertise that can be valuable in data analysis within scientific or industrial contexts.

What is a Chemistry Data Science job?

A Chemistry Data Science job involves applying data analysis, machine learning, and computational techniques to solve problems in chemistry. Professionals in this field work with large datasets from experiments, simulations, or literature to extract insights, optimize processes, and make predictions. Common applications include drug discovery, materials science, chemical informatics, and reaction optimization. This role typically requires expertise in chemistry, programming (e.g., Python, R), and statistical modeling.

What are the key skills and qualifications needed to thrive in the Chemistry Data Science position, and why are they important?

To excel in Chemistry Data Science, a strong background in chemistry combined with data analysis skills, usually evidenced by a degree in chemistry, chemical engineering, or a related field along with experience in statistics or data science, is essential. Familiarity with scientific computing, statistical programming languages like Python or R, and data visualization tools, as well as experience with cheminformatics databases, are typically required. Strong problem-solving, collaboration, and communication abilities set candidates apart in this interdisciplinary field. These skills are crucial for extracting actionable insights from complex chemical data, enabling informed decision-making and innovation in research or industry settings.

More about Chemistry Data Science jobs
What cities are hiring for Chemistry Data Science jobs? Cities with the most Chemistry Data Science job openings:
What are the most commonly searched types of Chemistry Data Science jobs? The most popular types of Chemistry Data Science jobs are:
What states have the most Chemistry Data Science jobs? States with the most job openings for Chemistry Data Science jobs include:
What job categories do people searching Chemistry Data Science jobs look for? The top searched job categories for Chemistry Data Science jobs are:
Chemistry Data Science jobs near you
Infographic showing various Chemistry Data Science job openings in the United States as of June 2026, with employment types broken down into 3% As Needed, 92% Full Time, 1% Part Time, 3% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Product Manager, Chemistry

Senior Product Manager, Chemistry

Revolution Medicines

Redwood City, CA

Other

Posted 13 days ago

Job description

The Opportunity:

We are seeking a Senior Product Manager, Chemistry to deliver products and capabilities that help Chemistry teams make faster, higher-confidence design and progression decisions in oncology-focused drug discovery.

This role will define and deliver the product strategy for Chemistry workflows, data products, and AI-enabled decision support using the right mix of internal product development, SaaS platforms, vendor partnerships, integrations, and RevCore capabilities. You will partner with medicinal chemists, synthetic chemists, computational chemists, analytical chemists, DMPK and Biology partners, Data Science, ML Engineering, Data Engineering, IT, and platform teams to turn complex Chemistry workflows into intuitive, scalable solutions that accelerate the Design-Make-Test-Learn cycle.

Own Chemistry product strategy

  • Define the vision and roadmap for Chemistry products and capabilities across medicinal chemistry, synthetic chemistry, analytical chemistry, compound management, and the Design-Make-Test-Learn cycle.

  • Build a Now, Next, Later roadmap from foundational compound data capabilities to self-service analytics, model-supported design, and AI-enabled decision support.

  • Set success metrics tied to trusted compound data access, reduced manual data preparation, faster design cycles, compound progression decisions, and scientific adoption.

Shape product solutions around Chemistry workflows and decisions

  • Understand workflows for medicinal chemists, synthetic chemists, computational chemists, analytical chemists, compound management teams, and cross-functional program teams.

  • Design solutions around key decision moments such as compound design, analog selection, route selection, synthesis planning, SAR interpretation, multi-parameter optimization, compound triage, and program prioritization.

  • Translate Chemistry workflows into clear product requirements, evaluation criteria, user stories, and prioritized capabilities.

  • Determine when to build, buy, partner, or integrate based on user needs, market capabilities, scalability, differentiation, interoperability, and long-term maintainability.

Establish trusted, reusable Chemistry capabilities and data products

  • Partner with technical teams, vendors, and SaaS providers to deliver priority Chemistry capabilities across RevCore and core Chemistry platforms.

  • Clarify trusted sources and systems of record for key Chemistry data, including compounds, structures, batches, lots, reactions, routes, analytical results, assay results, and calculated properties.

  • Improve structured data capture, data quality, metadata, and usability across Benchling, D360, legacy CDD data, compound registration, analytical systems, inventory systems, and related Chemistry platforms.

Enable self-service discovery, AI use cases, and adoption

  • Enable self-service access, compound search, structure search, SAR exploration, semantic discovery, and "Ask your Chemistry data" experiences across priority datasets.

  • Use modern AI, analytics, workflow, and low-code tools to prototype concepts, validate user needs, and de-risk ideas before full engineering investment.

  • Partner with Data Science and ML Engineering to identify and deliver AI and GenAI use cases such as chemistry copilots, SAR summarization, analog search, compound profile generation, synthesis-aware design support, and automated annotation

  • Drive rollout, adoption, and continuous improvement through usage metrics, feedback loops, training, and measurable workflow improvements.

Required Skills, Experience and Education:

  • 8+ years of experience in Product Management, Data Product Management, Chemistry Informatics, Cheminformatics, Scientific Data Platforms, or related roles within biotech, pharma, life sciences, or another research-intensive environment.

  • Strong product leadership experience, including defining vision, shaping strategy, building roadmaps, prioritizing tradeoffs, and delivering measurable outcomes.

  • Deep understanding of small molecule Chemistry workflows, including medicinal chemistry, Design-Make-Test-Learn, SAR analysis, compound progression, and multi-parameter optimization.

  • Experience translating scientific workflows into scalable product capabilities, user stories, evaluation criteria, and product requirements.

  • Working knowledge of Chemistry data and systems, including compound registration, structures, batches, reactions, analytical data, assay result integration, Benchling, D360, CDD, ELN, or related informatics tools.

  • Product judgment to evaluate build, buy, partner, and integration options based on user value, market maturity, scalability, interoperability, and maintainability.

  • Technical fluency across data platforms, integration, analytics, data quality, governance, metadata, and interoperability practices.

  • Strong communication and stakeholder management skills across scientific, technical, vendor, and business teams.

  • Ph.D., M.S., B.S., or equivalent experience in Chemistry, Medicinal Chemistry, Cheminformatics, Computational Chemistry, Bioinformatics, Computer Science, Engineering, Information Systems, or a related field.

Preferred Skills:

  • Experience establishing V1 data products, digital products, or foundational capabilities in a fast-moving biotech, pharma, or research environment.

  • Experience evaluating, implementing, or integrating SaaS platforms and vendor solutions for Chemistry, cheminformatics, analytics, or scientific workflow use cases.

  • Experience with AI-enabled molecular design, model-supported design workflows, cheminformatics, analog search, SAR tools, knowledge graphs, or multi-parameter optimization products.

  • Experience building self-service data access, compound search, structure search, SAR exploration, semantic discovery, natural language query, or "Ask your data" experiences for Chemistry users.

  • Experience using modern AI, analytics, workflow, and low-code tools to prototype product concepts, validate user needs, and de-risk ideas before full engineering investment.

  • Familiarity with chemistry data standards, molecular representations, controlled vocabularies, metadata standards, FAIR data principles, and scientific data interoperability approaches.

  • Comfort operating in an emerging biotech environment where strategy, execution, ambiguity, evolving scientific needs, vendor complexity, and hands-on problem solving all matter. #LI-Hybrid  #LI-YG1

Apply