Associate Director, AI Policy and Channel

Bristol Myers Squibb • Princeton, NJ

2d

About The Position

Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us . Role Overview The Associate Director, Artificial Intelligence, Policy and Channel (AIPC) is a senior technical leader who sits at the intersection of advanced data science and commercial strategy at BMS. This role goes beyond hands-on technical delivery — it requires the ability to shape how AI and machine learning are applied across BMS's commercial operations, while leading a team and driving broad organizational adoption. The Associate Director provides AI-driven insights that help BMS anticipate and respond to channel-level business trends, payer contract dynamics, legislative policy shifts, and new indication launches. In a rapidly evolving reimbursement and pricing landscape, this role is critical for maintaining BMS's agility and effectiveness across Market Access and Commercial operations. The Associate Director acts as a key bridge between technical teams and senior business stakeholders, translating complex analytical outputs into commercial decisions that matter.

Requirements

• Bachelor's degree (BA/BS) in a quantitative field — Data Science, Computer Science, Mathematics, Statistics, Engineering, or equivalent.
• Minimum 5–7 years of hands-on experience developing and deploying machine learning solutions to solve complex, real-world business problems.
• Demonstrated experience leading technical teams or projects with measurable business outcomes.
• Proven track record of managing AI product lifecycles, from concept through deployment and iteration.
• Programming Python (required); R or other statistical languages (a plus)
• Machine Learning TensorFlow, PyTorch, scikit-learn; supervised, unsupervised & reinforcement learning
• Forecasting Time series forecasting, Monte Carlo simulations
• Statistical Methods Strong foundation in applied statistics for business problems
• MLOps & Cloud CI/CD, Git/GitHub, MLOps workflows, AWS/Azure, Airflow/Dagster
• Strategic Thinking: Ability to connect technical work to broader commercial goals and organizational strategy.
• Communication Excellence: Proven ability to communicate complex technical topics clearly to non-technical audiences, including senior leadership.
• Stakeholder Influence: Strong interpersonal skills with a track record of building relationships and driving alignment across functions.
• Ownership and Accountability: Takes initiative, drives projects to completion, and holds themselves and their team to high standards.
• Adaptability: Comfortable navigating ambiguity and adjusting approaches in response to new data, policy changes, or shifting priorities.
• Inclusive Leadership: Committed to building a respectful, collaborative, and inclusive team environment.

Nice To Haves

• Advanced degree (MS or Ph.D.) in Computer Science, Computational Biology, Bioinformatics, Data Science, or a closely related field.
• Experience in biopharmaceutical, healthcare, or similarly complex commercial environments is strongly preferred.
• NLP, LLMs (training/fine-tuning), agentic AI frameworks (preferred)
• Deep understanding of biopharmaceutical market access, pricing, value demonstration, and the reimbursement landscape.
• Familiarity with channel dynamics, payer contracting mechanisms, and the legislative policy environment affecting pharmaceutical commercialization.
• Experience operating effectively in matrixed organizations and driving outcomes across teams without formal authority.

Responsibilities

• Technical Leadership and ML Pipeline Development Architect and Oversee ML Pipelines: Lead the design, development, and deployment of scalable, end-to-end machine learning pipelines that solve critical business challenges in Market Access, Pricing, and Value Demonstration.
• Drive Technical Standards: Set and enforce best practices for reliability, scalability, and maintainability across all deployed solutions, including CI/CD workflows, version control (Git/GitHub), MLOps, and workflow orchestration.
• Apply Advanced Modeling Techniques: Direct the application of time series forecasting, Monte Carlo simulations, supervised/unsupervised learning, and emerging technologies such as NLP and Large Language Models (LLMs) to commercial business problems.
• Automate and Scale: Oversee the automation of complex data workflows (e.g., biopharmaceutical rebates, contracts, government policies), ensuring solutions are robust and ready for real-time decision support.
• Stay Ahead of the Curve: Proactively evaluate and introduce new AI/ML technologies and frameworks that can strengthen BMS's commercial analytics capabilities.
• Strategic Program Oversight Translate Strategy into Delivery: Work closely with the Director, AIPC to execute on the multi-year AI program roadmap, ensuring individual workstreams are aligned with commercial priorities and organizational goals.
• Manage Competing Priorities: Balance technical delivery, innovation, and resource allocation across multiple concurrent projects, ensuring focus remains on high-impact outcomes.
• Drive the GTN AI Accelerator: Play a lead role in extending the GTN AI Accelerator across BMS's portfolio — scaling forecasting models to additional brands, payer channels, and product archetypes (e.g., specialty pharmacy, medical benefit).
• Governance and Compliance: Support adherence to program governance standards, regulatory requirements, and budget targets across all AI initiatives.
• Stakeholder Engagement and Cross-Functional Collaboration Build Strategic Partnerships: Cultivate strong, trust-based relationships with cross-functional teams including Business Insights & Technology, Commercialization, Finance, Brand, and Market Access groups to co-develop solutions that align with business priorities.
• Lead Requirements Gathering: Engage directly with brand finance directors, pricing and access leads, and forecasting teams to define AI solution requirements and ensure outputs meet real business needs.
• Bridge Technical and Business Worlds: Serve as the primary liaison between technical teams and non-technical senior stakeholders, translating model results and insights into clear, decision-ready strategies.
• Drive Adoption: Champion the integration of AI tools into core business workflows, ensuring stakeholders understand, trust, and actively use AI-driven insights in their decision-making.
• Executive Communication: Present confidently to senior leadership and diverse stakeholder groups, clearly communicating model performance, business impact, and strategic implications.
• AI Product Lifecycle Management Own the Full Lifecycle: Take end-to-end ownership of AI products — from initial ideation and requirements definition through development, deployment, integration, and ongoing performance monitoring.
• Plan and Execute Delivery: Develop detailed project plans that align with business timelines, ensuring high-quality delivery against key milestones (e.g., integration into the Anaplan forecasting platform, rollout to new brands).
• Measure and Improve: Conduct post-deployment impact analysis to validate business value and drive continuous improvement through structured stakeholder feedback loops.
• Adapt to Change: Incorporate evolving market data, policy changes, and new commercial priorities into existing models and solution roadmaps.
• Team Leadership and People Development Lead Technical Projects: Drive technical projects from conception through delivery, ensuring alignment with business goals and technical excellence throughout.
• Mentor and Guide: Provide technical guidance and mentorship to junior data scientists and analysts, fostering a culture of learning and innovation.
• Foster a Learning Culture: Create an environment that encourages knowledge sharing, experimentation, and continuous skills development, consistent with BMS's people values.
• Enable Matrixed Collaboration: Effectively collaborate across teams and influence outcomes without formal authority, driving delivery across organizational boundaries.
• Support Talent Acquisition: Partner with the Director, AIPC on hiring plans, candidate evaluation, and onboarding of new team members.

Benefits

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life benefits include: Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day. All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees