Manager, Manufacturing Optimization Analytics

Position Summary

The Manufacturing Optimization Analytics (MOA) team within Business Insights and Technology (BI&T) partners with the Bristol-Myers Squibb manufacturing operating units (Pharmaceuticals, Biologics, and Cell Therapies) to support data analytics for all key functions within the operating units. MOA focuses on answering key business questions that drive prioritized business decisions using advanced analytics, data science, and AI. The manufacturing operating units at Bristol-Myers Squibb support the manufacture of all products, technology transfer, quality release, and distribution to patients.

Their scope includes portfolio strategy, clinical supply manufacturing and distribution, network strategy, brand strategy, drug substance manufacturing, vector manufacturing, drug product manufacturing, commercial supply and distribution, and analytical development for all assets. The MOA group supports business analytics across this entire value chain.

• Supporting Business Decisions
  • Work closely with business stakeholders to proactively identify and address priority business questions within the member functions.
  • Drive the application of fact-based decision making for key questions within the business and portfolio deliverables enabling priority business choices.
  • Develop a deep understanding of the member functions’ business priorities.
  • Build relationships with key stakeholder and senior leaders within the functions and Business Insights and Technology.
  • Demonstrate ability to influence senior leaders to adopt analytics-derived insights and automated, AI platforms.
• Driving Analytics and Capabilities
  • Design, develop and implement a broad array of business analytics that solve complex problems in a computationally efficient and statistically appropriate manner.
  • Identify new opportunities to further leverage analytics, data, analytical tools, and AI.
  • Actively manage multiple projects in parallel from charter through completion.
  • Ensure best practice adoption within stated areas of responsibility, applying appropriate levels of technical capability, standardization and subject matter expertise.
  • Define standards for the provision of analytics to support planning and decision making processes, and utilizes appropriate escalation processes.
  • Act as subject matter expert of the Bristol-Myers Squibb technology stack within team and provide technical leadership for driving technology solutions in analytics deployment.
  • Drive capability build for data automation, cloud computing, data lake integration, scalable software platforms, and AI within team.
  • Contribute to defining the overall team strategy in collaboration with team leadership.
• Driving Team Productivity and Operational Excellence
  • Conduct detailed team walkthroughs and peer review of team’s work to ensure quality, cross-training and knowledge management within the team.
  • Lead standardization of analytics and process methodologies in PDS Analytics Development.
  • Authors detailed documentation that describes analytics tool development, assumptions and input data and data processing. Authors user manual for dissemination within stakeholder user base.
  • Guides external consultants in adoption of standards.

Minimum Qualifications

• Ph.D. in engineering, pharmaceutical science, chemistry, biochemistry, physics or other quantitative area of study with 0-1 years of experience.
• M.S in engineering, pharmaceutical science, chemistry, biochemistry, physics or other quantitative area of study with 1-3 years of experience.
• B.S. in engineering, pharmaceutical science, chemistry, biochemistry, physics or other quantitative area of study with more than 3 years of experience.
• 3+ years hands‑on working in the area of data science, data analytics, data integration, reporting.
• 3+ years of hands‑on experience with data science and analytics, modeling platforms, data engineering software and visualization tools (e.g. Advanced SQL, PL/SQL, R, Python, SAP HANA, PowerBI, Redshift, Postgres, AWS Cloud, Athena, etc.).
• Ability to architect analytic and data science solutions, including platform software solutions, and AI.

Experience

• Excellent interpersonal,…