Director, Scientific Data

Drug Hunter

. Serve as the primary internal subject-matter expert for cheminformatics and scientific data, with sufficient breadth across bioinformatics and drug discovery data to guide data decisions spanning chemistry and biology.

Posted 10/9/2026full-timeRemote • Massachusetts • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in cheminformatics and bioinformatics, with a strong focus on data strategy, quality, and integration in drug discovery. Proficient in data modeling, scientific semantics, and leading cross-functional teams to drive data-driven decisions.

Highest-signal resume keywords

PhD In Cheminformatics10+ Years In Scientific DataData Modeling SkillsProficiency In Python And SQLFluency In Bioinformatics

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cheminformatics LiteracyMolecular RepresentationsStructure StandardizationSubstructure/Similarity SearchData Quality StandardsEntity ResolutionOntology StrategyData PipelinesData ToolingScientific Data Evaluation

Soft Skills

Clear CommunicationLeadershipMentorshipCollaborationProblem-Solving

Tools & Technologies

RDKitBiological DatabasesData ModelsCuration StandardsControlled Vocabularies

Industry Keywords

Drug DiscoveryBiotechLife Science DataDMPKClinical Domains

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Serve as the primary internal subject-matter expert for cheminformatics and scientific data, with sufficient breadth across bioinformatics and drug discovery data to guide data decisions spanning chemistry and biology.
Own the scientific strategy for how Drug Hunter acquires, represents, integrates, normalizes, and maintains scientific data, partnering with Engineering and Science on architecture and curation processes.
Define how chemical entities are represented, registered, standardized, and resolved across sources, and establish curation standards, controlled vocabularies, QA rules, and scalable tooling.
Define approaches for extracting structured scientific information from unstructured literature and patent content, including chemical structures, text, and tables, and link extracted information to canonical entities.
Own scientific semantics, entity resolution, and ontology strategy across compounds, targets, genes, diseases, organizations, assays, and other concepts.
Evaluate scientific data sources across chemistry, biology, DMPK, drug, and clinical domains, including coverage, quality, overlap, limitations, licensing, and update characteristics.
Establish standards for data quality, provenance, validation, completeness, and freshness, and ensure effective data-quality issue resolution processes.
Partner with Science to translate scientific expertise and curation decisions into maintainable data models, standards, and processes.
Partner with Engineering on data models, technical approaches, architectural decisions, and trade-offs involving scientific information and application systems.
Partner with Product Management to translate scientific and technical requirements into project specifications and communicate technical trade-offs.
Evaluate build-versus-buy decisions for scientific datasets, cheminformatics and bioinformatics capabilities, and data tooling.
Lead the Data team in translating priorities into executable projects while understanding progress, challenges, dependencies, and workload.
Provide scientific and technical leadership, mentorship, and direction to the Data team, including creating, hiring, and managing roles as needed.

Requirements

What you’ll need

PhD in cheminformatics, bioinformatics, computational biology, structural biology, or a related quantitative life-science field.
10+ years working with scientific data in drug discovery, biotech, or life science data/informatics companies, including 3+ years leading people or a data function
Working cheminformatics literacy (molecular representations, structure standardization, substructure/similarity search concepts, RDKit or similar tools)
Fluency in bioinformatics, with a deep working knowledge of biological databases and ontologies, target and pathway biology, and gene/protein identifier mapping
Strong data modeling skills and hands-on proficiency in Python and SQL; experience with data pipelines and modern data tooling
Understanding of the drug discovery process from target to clinic, and ability to converse fluently with medicinal chemsits and biologists
Clear communicator who can move seamlessly between scientific details and engineering/product trade-offs

Benefits

Comp & perks

Competitive salary, variable compensation, and equity
Broad range of medical, dental, vision, and life insurance plans for employees and their dependents, including generous coverage for a platinum PPO healthcare plan
Short-term disability and long-term disability insurance
Cancer and critical illness coverage
Up to 14 weeks paid parental leave (after 1 yr tenure) and childcare FSA plan
401(k) + employer match
Home office set up stipend for fully remote employees
Learning and development support
Generous and flexible vacation and leave policies