Senior Director, Manufacturing Optimization and Risk Analytics
Description
At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.
Position Summary:
Product Development and Supply (PDS) Business Insights & Technology (BI&T) is transforming how the organization uses data, analytics, and Applied AI to accelerate the delivery of medicines to patients. As part of this evolution, PDS BI&T Analytics Development is moving from delivering local, bespoke analyses to delivering durable Analytics Products, models, and tools that let both people and AI unlock insights across PDS, built by small, rapidly deployed teams embedded with business experts.
Are you energized by the challenge of making manufacturing more efficient while reducing the risk of quality failures and supply disruption? Do you know how to combine numerical optimization, predictive modeling, and Applied AI to solve problems at global scale? Are you equally comfortable leading a large, distributed team of data scientists and analytics professionals and holding your own with senior manufacturing, quality, and technology executives? If so, this role might be for you.
The successful candidate will be an experienced analytics and data science leader who can set the technical direction for a global team and partner with executives across PDS to turn analytics into better decisions on the manufacturing floor. This individual will lead the Manufacturing Optimization and Risk Analytics team, which builds tools that help PDS manufacture as efficiently as possible by using optimization, variability projection, advanced analytics, and Applied AI to predict and mitigate risk across Quality, Equipment, Technology, and Process. This role will lead a global team of 17-22 analytics and data science professionals supporting all PDS manufacturing sites, including a team leader focused on Quality and Manufacturing Risk, and will partner closely with CTDO, GBU, GQ, and GTS.
Key Responsibilities
Lead the Manufacturing Optimization and Risk Analytics Team
- Lead, manage, and coach a global team of 17-22 data scientists, analytics professionals, and team leaders supporting all PDS manufacturing sites, building a high-performing, inclusive team and developing the next generation of leaders
- Give team members autonomy to prioritize and more room to deliver new capabilities, while ensuring work is aligned to the PDS Digital strategy and Prioritized Digital Products
- Shape the team structure as the organization evolves toward product-centric development, balancing skills across data science, business acumen, and Applied AI
- Drive the shift from bespoke analysis to reusable Analytics Products, instilling a customer-centric, outcomes-driven mindset and embracing small, embedded Fusion team models for rapid delivery
Provide Technical Leadership in Data Science and Analytics
- Set the technical vision and standards for numerical optimization, variability projection, predictive risk modeling, and Applied AI across the portfolio, ensuring methods are rigorous, explainable, and fit for use in a regulated manufacturing environment
- Guide the team in adopting agentic coding tools and modern data infrastructure to increase delivery speed, reuse, and the quality of analytics solutions
- Review and challenge technical approaches, model design, validation, and performance monitoring, and serve as the escalation point for complex problems
- Build Applied AI capabilities that embed directly in PDS decision making, enabling both people and AI to surface insights and act on them
- Stay current on advances in data science, optimization, and AI, and bring proven external practices into the team
Reduce Quality, Equipment, and Delivery Risk in Manufacturing
- Direct the development of tools that predict and mitigate disruption risk arising from variability in Technology, Quality, Equipment, and Process, helping sites protect product quality and on-time delivery to patients
- Lead efforts to optimize manufacturing processes, capacity, and scheduling, identifying and quantifying opportunities to improve efficiency, yield, and throughput
- Partner with manufacturing sites to understand their most critical challenges, and deploy analytics products that are adopted, trusted, and used in daily operations
- Define and track measurable value delivered, including risk reduction, efficiency gains, and avoided disruption, and communicate results to PDS leadership
Partner with Executives and Stakeholders Across PDS
- Build and sustain trusted relationships with senior leaders in CTDO, GBU, GQ, and GTS, as well as site leadership, to understand priorities and align analytics investments to business value
- Collaborate with the End-to-End Value Chain Analytics team and other BI&T teams to integrate products across PDS pillars and avoid duplication
- Build consensus through the facilitation of productive discussions, ensuring all voices are heard and understood, and resolve prioritization trade-offs across sites and functions
- Represent PDS BI&T - Analytics Development in cross-functional and BI&T-wide forums, contributing to enterprise standards for analytics, data, and AI
- Demonstrate collaboration and proactiveness across the digital transformation team; embrace a "no task is too big or small" mindset
Requirements
- Bachelor's degree required in data science, statistics, engineering, operations research, computer science, or similar quantitative discipline; advanced degree (Master's or PhD) preferred
- 12+ years of experience in data science, advanced analytics, or operations research, including 5+ years directly managing data science or analytics teams and people leaders
- Experience leading globally distributed teams across multiple sites or time zones
- Demonstrated technical depth in applied machine learning, optimization, and statistical modeling, with the judgment to guide a team and evaluate approaches in a hands-on way
- Experience applying analytics to manufacturing, supply chain, quality, or other operational problems, preferably in pharmaceutical, biotech, or other regulated industries
- Working knowledge of Applied AI and modern delivery practices, including generative AI and agentic coding tools, and a track record of turning models into adopted products
- Proven ability to build relationships and influence executive stakeholders across functions, translating business challenges into analytics solutions and demonstrating measurable value
- Experience building reusable analytics products and shifting teams from bespoke analysis toward product-based ways of working
- Enthusiasm and energy to help transform organizations, with tenacity and perseverance for leading change
- Excellent communication and presentation skills, with the ability to communicate complex ideas to stakeholders at all levels of the organization
Why you should apply
- You will help patients in their fight against serious diseases
- You will be part of a company that encourages excellence and innovation, respects diversity, develops leaders and values its employees.
- You’ll get a competitive salary and a great benefits package including, but not only, an annual bonus, pension contribution, family health insurance, 27 days of annual leave , access to BMS Cruiserath on-site gym and life assurance
We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.
How We Work
Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.
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