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Job Function:
Data Analytics & Computational Sciences
Job Sub Function:
Data Science
Job Category:
People Leader
All Job Posting Locations:
Cambridge, Massachusetts, United States of America
Job Description:
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.
Key Responsibilities
Strategy & Vision
- 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.
Autonomous Learning & Closed‑Loop Systems
- 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).
Models, Platforms & MLOps
- 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.
Cross‑Functional Collaboration
- 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.
Leadership & Talent Development
- 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.
Qualifications
- 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.
Leadership Attributes
- 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.
Ready to make an impact? Join us in shaping the future of Autonomous Learning in Therapeutic Discovery at Johnson & Johnson.
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 & 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, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.
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Required Skills:
Preferred Skills:
Advanced Analytics, Budget Management, Compliance Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Program Management, Strategic Thinking, Succession Planning
The anticipated base pay range for this position is :
$164,000.00 - $282,900.00
Additional Description for Pay Transparency:
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
