Job Information
Bristol Myers Sqibb BMS Associate Director, AI Policy and Channel - Princeton NJ in Princeton, New Jersey
469342BR
Auto req ID:
469342BR
Company:
Bristol Myers Sqibb BMS
Job Code:
Pharmaceutical Pharmaceutical
Job Description:
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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.
Key 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.
Position Title:
Associate Director, AI Policy and Channel - Princeton NJ
Job Category:
Director
Minimum Education Required:
Bachelors
City*:
Princeton
Additional Qualifications/Responsibilities:
Qualifications
Education
Required: Bachelor's degree (BA/BS) in a quantitative field — Data Science, Computer Science, Mathematics, Statistics, Engineering, or equivalent.
Preferred: Advanced degree (MS or Ph.D.) in Computer Science, Computational Biology, Bioinformatics, Data Science, or a closely related field.
Experience
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.
Experience in biopharmaceutical, healthcare, or similarly complex commercial environments is strongly preferred.
Technical Skills
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
Advanced AI
NLP, LLMs (training/fine-tuning), agentic AI frameworks (preferred)
Soft Skills and Competencies
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.
Preferred Expertise
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.
Compensation Overview:
Princeton - NJ - US: $167,540 - $203,013
State*:
New Jersey
Salary Range:
$100,000