Associate Director, R&D Data, Data Science and AI - Data Strategy and Products

Johnson & Johnson Innovative Medicine • Hopewell Township, NJ

4d • Hybrid

About The Position

Johnson and Johnson Innovative Medicine (J&J IM), a pharmaceutical company of Johnson & Johnson is recruiting for an Associate Director, R&D Data, Data Science and AI - Data Strategy and Products. The primary location for this position is flexible – either; Titusville, NJ; Spring House, PA; San Diego, CA; Boston, MA. Remote work options may be considered on a case-by-case basis and if approved by the company. An pre-identified candidate for consideration has been identified. However, all applications will be considered. 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 R&D Data Science Digital Health - Data Strategy and Products – Associate Director will contribute to the design and execution of a comprehensive, cross-Therapeutic Area -focused data strategy program designed to accelerate research, R&D insights and evidence generation. Combining strategic planning with hands on execution within our federated organizational structure, this director will embed closely across verticals to understand the “what” and the “why,” while spending most the time driving the “how.” This involves acting as the connective tissue between teams -- identifying scientific data assets, coordinating the building of biomedical data products, evaluating data availability and applicability while operationalizing capabilities across the product lifecycle. This individual will act a trusted, partner to the broader Data Science Digital Health team, bridging the intersection of clinical and computational needs, and ensuring data fit and availability for scaling solutions across the organization.

Requirements

• A minimum of 8 years of experience in pharma/biomedical R&D or commercial functions, with significant exposure to diverse biomedical data assets management, procurement, and/or strategy; or 6+ years of experience with an advanced degree.
• Demonstrated scientific excellence in biomedical R&D through consistent publishing as a lead author in the domains of bioinformatics, knowledge graphs and data science.
• Deep experience with data quality control in high-stakes pharmaceutical or clinical domains, and regulatory requirements around healthcare data.
• Prior experience and proven track record with leading multidisciplinary teams and influencing cross-functional stakeholders without direct authority.
• Experience should include direct responsibility for data products spanning multiple disease domains/therapeutic areas.
• Expertise in discovery-stage omics data (e.g., genomics, transcriptomics, proteomics, epigenetics, high-throughput screening) and how to connect these assets to translational biomarkers, clinical endpoints, downstream real-world evidence, and R&D needs.
• Demonstrated experience constructing large-scale knowledge graphs/ontologies, including integration across pharmaceutical and/or healthcare domains.
• Understanding of semantic web technologies (SPARQL, RDF, OWL) and experience leveraging graph databases (e.g., Graphwise GraphDB, Neo4j) to solve biomedical problems.
• Proven experience working with complex multimodal biomedical datasets, including genomics, proteomics, imaging, phenotypic, and high-throughput screening data.
• Proficiency working with common bioinformatics file formats (e.g., FASTQ, BAM/SAM, differential expression and QC reports) across multiomic assays, and an understanding of the critical metadata associated with assay development including wetlab, pipeline execution, quality control parameters
• Hands-on experience managing teams collaborating using using Git and CI/CD platforms (Jenkins, Bitbucket/GitHub), DevOps tooling, metrics/monitoring, and container technologies (Docker/Singularity), for reproducible data science.
• Strong ability to translate complex technical work into business recommendations for cross-functional and senior stakeholders.
• Pragmatic problem solving — focus on delivering usable outcomes quickly and iterating.
• Strategic thinker who can connect tactical work to long‑term business goals.
• High standards for data quality, reproducibility, and documentation.
• Comfort working in ambiguity and shaping new capabilities at scale.

Nice To Haves

• Experience designing observational studies, cohort design, survival analysis, or clinical trials statistics and communicating limitations is a plus.

Responsibilities

• Define a multi‑year vision and roadmap for enterprise knowledge management through knowledge graphs, aligned with R&D priorities and therapeutic area strategies.
• Drive prioritization of omics, clinical, and experimental (ELN) knowledge integration based on scientific impact, translational value, and speed‑to‑insight.
• Establish clear lifecycle governance for knowledge graph assets, ensuring sustained scientific relevance, quality, and reuse across programs.
• Lead the design, development, and stewardship of semantically rich biomedical data models that unify heterogeneous omics, clinical trial, and experimental data into AI‑ready knowledge graphs firmly grounded in biochemistry.
• Partner with data engineering and platform teams to build, scale, and operate high‑performance knowledge graph services, enabling advanced querying, retrieval, and downstream analytics across therapeutic areas.
• Orchestrate the creation of rich metadata, lineage, and provenance documentation, ensuring trust, reproducibility, and scientific interpretability of knowledge assets.
• Partner with advanced analytics and artificial intelligence teams to enable knowledge‑graph‑aware discovery, and insights generation across R&D use cases.
• Collaborate with scientific, clinical, and technical stakeholders to translate complex biomedical questions into knowledge‑product‑driven solutions that span omics, trials, and experimental domains.
• Communicate knowledge graph strategy, maturity, and impact to senior leadership, supporting data‑driven R&D and portfolio decisions.
• Foster cross‑functional collaboration, shared standards, and best practices for knowledge contribution and stewardship, integrating domain expertise, bioinformatics, and data science at scale.

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 period
• 10 days Volunteer Leave – 32 hours per calendar year
• Military Spouse Time-Off – 80 hours per calendar year

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree