Director of AI Optimization and Productization - R&D Data Science & Digital Health

Johnson & Johnson
High Wycombe
2 months ago
Applications closed

Related Jobs

View all jobs

Director, Quantitative Imaging or Imaging Biomarkers (City of London)

Director, Quantitative Imaging or Imaging Biomarkers

Director, Quantitative Imaging or Imaging Biomarkers (London Area)

Director, Quantitative Imaging or Imaging Biomarkers

Head of Data Analytics

Manager Quantitative Analysis - Centre for UK Growth

Job Function

Data Analytics & Computational Sciences


Job Sub Function

Data Science


Job Category

People Leader


All Job Posting Locations

High Wycombe, Buckinghamshire, United Kingdom


Job Description

Johnson & Johnson Innovative Medicine (IM) is recruiting for a Director of AI Optimization and Productization - R&D Data Science & Digital Health. This position can be located in Titusville, NJ; Spring House, PA; La Jolla, CA; Cambridge, MA or London, United Kingdom. This position will require up to 25% travel.


For candidates based in the US, please use Req: R-035871


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


About the Role

We are looking for an experienced technical, hands‑on, leader in AI optimization and productization to join our Data Science & Digital Health (DSDH) team within Research & Development (R&D). This role reports directly to the Vice President of AI/ML & Digital Health. The team will support the training, optimization, and deployment of AI models and AI products across the R&D value chain. In close collaboration with Johnson & Johnson Technology (JJT), this leader will leverage enterprise MLOps and DevOps frameworks to implement good AI development practices and life cycle management across DSDH AI projects. A key focus will be optimizing AI models and code for large-scale training, inference performance, and product deployment, working alongside JJT and external partners. Additionally, the role will guide the development of AI applications in areas such as discovery, biomarkers, and clinical endpoints. This leader will engage across the enterprise, partnering with DSDH teams, JJT, and therapeutic areas within J&J Innovative Medicine R&D, while also interfacing with senior stakeholders throughout the organization.


Responsibilities

  • Collaborate with AI scientists in DSDH, R&D partners, and JJT to optimize AI models for large-scale training, inference performance, and their deployment in AI products.
  • Guide and supervise the productization of AI models into applications deployed within R&D or clinical trials for discovery, biomarkers, and clinical endpoints.
  • Oversee the use of enterprise MLOps frameworks within DSDH in close collaboration with JJT, following company best practices and frameworks and managing the life cycle of DSDH AI models.
  • Actively modeling and planning for compute capacity across DSDH projects, in partnership with the DSDH Data Strategy & Platform team and JJT.
  • Work closely with DSDH, JJT, therapeutic areas, functions, and senior stakeholders across the enterprise to promote cross-functional collaboration and stakeholder engagement.
  • Attract, grow, and lead a high-performing technical team focused on AI optimization, productization, and life cycle management.
  • Mentor junior team members and foster a culture of continuous learning.

Qualifications

  • Advanced degree (PhD or Master’s) in Computer Science, Machine Learning, Biomedical Engineering, or a related field. Additional training or certification in MLOps, AI optimization, product life cycle is a plus
  • 8+ years of experience in AI model development, model optimization, and deployment, including managing product life cycle (design, development, testing, deployment, operations & maintenance, etc.).
  • Excellent coding and software development capabilities, effectively leading a technical team and partners towards the creation of scalable AI solutions.
  • Deep expertise in using MLOps frameworks, deployment pipelines, and monitoring tools, including familiarity with cloud platforms and containerization tools. Experience with AWS is preferred.
  • Experience with Agile and DevOps methodologies
  • Experience with regulatory compliance and governance (e.g. GxP, SaMD, etc.).
  • Strong experience in leading a technical team, and ability to work in a matrixed organization on complex, multi-stakeholder projects
  • Excellent communication skills and strategic thinking capabilities.
  • Ability to align technical execution with strategic business goals and enterprise-wide initiatives and frameworks.
  • Experience in Life Sciences, Healthcare, Pharmaceutical or Medical Tech sector is preferred

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 and 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, please email the Employee Health Support Center () or contact AskGS to be directed to your accommodation resource.


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


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.