Director, Data Science - DDSAI - Therapeutics Discovery

Johnson & Johnson Innovative Medicine • Cambridge, MA

1d • $164,000 - $282,900 • Onsite

About The Position

Johnson & Johnson Innovative Medicine is recruiting for a Director, Data Science - DDSAI - Therapeutics Discovery. This position has a primary location of Cambridge, MA. 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

Role Overview
We are seeking a Director within our Data, Data Science, & AI (DDSAI) organization to lead the design, development, and deployment of Autonomous Learning and Closed‑Loop Optimization capabilities across the Therapeutics Discovery (TD) organization. This role will bring together data generated from lab equipment, computational and predictive models, and MLOps infrastructure into an integrated learning loop that continuously informs the experiments we should execute next, experimental data analysis, aid molecule synthesis and experiment execution. The Director will partner closely with TD scientific leaders, in silico discovery teams, IT, and other data science teams to enable self‑improving discovery systems—ranging from human‑in‑the‑loop decision support to fully closed‑loop experimental optimization. This role requires a leader who can translate cutting‑edge AI, optimization, and automation concepts into robust, scalable, and trusted discovery capabilities aligned with TD priorities and interoperable across our lab activities in other functions including PSTS, TDS, and our Therapeutic Areas.

Requirements

• PhD or equivalent experience in Computational Biology, Chemistry, Engineering, AI/ML, Applied Mathematics, Statistics, or a related field.
• 8–12+ years of experience applying data science and AI in drug discovery or adjacent scientific domains, with demonstrated leadership in matrixed environments (experience range adapted for Director level).
• Proven expertise in deploying ML/AI models integrated with experimental or operational systems.
• Strong understanding of drug discovery workflows, laboratory data generation, and experimental decision‑making.
• Experience with MLOps, model governance, and scalable data platforms in regulated or high‑stakes environments.
• Exceptional communication skills, with the ability to influence scientific, technical, and executive stakeholders globally.

Nice To Haves

• Strategic Vision: Ability to anticipate future trends in data science and drug discovery and translate them into actionable strategies.
• Collaborative Influence: Skilled at building consensus and driving alignment across diverse scientific and technical teams.
• Innovation Mindset: Passion for leveraging emerging technologies to solve complex scientific challenges.
• Talent Development: Commitment to mentoring and growing a high-performing team of data scientists and engineers.
• Communication Excellence: Ability to articulate complex technical concepts to non-technical stakeholders and executive leadership.

Responsibilities

• Define and execute the TD Autonomous Learning strategy, establishing a clear roadmap for closed‑loop discovery, adaptive experimentation, and continuous model improvement across TD.
• Identify high‑value discovery use cases where learning loops can accelerate decision‑making, improve experimental efficiency, and enhance molecule design outcomes.
• Partner with TD and DPDS leadership to ensure alignment with broader R&D data, AI, and digital health strategies.
• Lead the integration of lab instrumentation data, assay systems, and automation platforms with predictive models and optimization algorithms.
• Develop and scale closed‑loop and human‑in‑the‑loop workflows that connect: Experiment Execution Data capture and curation Model training, inference, and uncertainty estimation Experimental and molecular design recommendations
• Drive the adoption of design‑of‑experiments (DoE), Bayesian optimization, active learning, and reinforcement learning approaches where appropriate (role adaptation).
• Partner with data science and engineering teams to ensure models are production‑grade, reproducible, and monitored through robust MLOps and model lifecycle management practices.
• Champion FAIR data principles, interoperability, and responsible AI within autonomous discovery systems.
• Ensure seamless integration with enterprise data platforms and downstream analytics capabilities.
• Collaborate deeply with TD groups such as In Silico Discovery and Discovery Technologies & Molecular Pharmacology, as well as IT and R&D Data Science partners, to embed autonomous learning into real discovery workflows.
• Work with peers across Discovery, Product Development & Supply (DPDS), and Therapeutic Areas to scale successful approaches beyond TD.
• Build external partnerships with academic and industry leaders in autonomous discovery and laboratory automation.
• Lead and grow a multidisciplinary team spanning data science, optimization, ML engineering, and scientific computing.
• Foster a culture of scientific rigor, experimentation, and continuous learning.
• Mentor talent to bridge scientific, computational, and operational perspectives in discovery.

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
• 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