Associate Director - US Predictive Customer Engagement

About this role

Working with Us 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 .

Description: Predictive Customer Engagement team is responsible for developing and evolving the customer engagement AI capabilities to support decision-making and execution by scaling advanced data processing, novel reasoning patterns, and intelligent activities across marketing, field engagement optimization, and omnichannel experience orchestration. As an Associate Director on the team, you will lead the end-to-end development of AI capabilities—spanning the HCP 360 data foundation, field engagement recommendation/optimization, NPP/HOE & 3PP orchestration, and ensure these capabilities are productionized reliably, responsibly, and at enterprise scale.

Key Responsibilities   1) AI/ML Product & Technical Leadership • Own technical direction for AI capabilities that prioritize the right customer, content, journey/channels, and insights—and enhance capability maturity over time. • Lead development of predictive and optimization components that translate HCP-level signals into engagement recommendations and insights. • Drive “explainable AI” packaging so recommendations include interpretable drivers/insights that support pre-call planning and confidence.

2) Data & Feature Engineering for the HCP 360 Foundation • Oversee engineering patterns for the “360 HCP dataset / data cube” that underpins the AI engine —ensuring reliability, lineage, and fit-for-purpose feature sets. • Partner with upstream data teams and internal stakeholders to integrate new data feeds (e.g., patient opportunity inputs, engagement signals) into model-ready feature layers.

3) MLOps / DevOps / Production Excellence • Lead production operationalization—covering refresh steps, runs, publishes, and cross-TA/brand workflows (bi-weekly, HOE, 3PP/digital, etc.). • Establish strong engineering hygiene: CI/CD, code quality, standardized tooling, and repeatable release processes (e.g., consolidated linting/formatting and PR-based workflows). • Drive reduction of “hotfix-as-BAU” by improving design patterns, backlog discipline, and root-cause remediation.

4) Governance, Risk, and Responsible AI • Ensure AI enhancements follow required governance controls and risk review processes; coordinate artifacts and timelines so launches are not blocked by minimum assessment windows. • Embed compliance needs into system behavior (e.g., suppression/opt-out handling discussions and related operational considerations).

5) Stakeholder Partnership & Delivery Leadership • Serve as the technical counterpart to product/strategy stakeholders—translating business needs into prioritized, feasible engineering work (e.g., business request intake and delivery). • Lead cross-functional working sessions to define hypotheses, pressure-test insights, finalize language, conduct system integration testing, and enable field readiness for launch.

6) Team Leadership & Talent Development • Coach and develop engineers/data scientists; set technical standards; create a culture of operational excellence, high-quality documentation, and continuous improvement.

Qualifications Required: • BA/BS degree (quantitative area of study preferred) • Minimum of 5 years of hands-on relevant experience in life science and healthcare industries (including data engineering, data science projects, designing, developing and deploying ML models) • Proficiency in python, SQL, spark, git, MLOps • Solid understanding of LLM, genAI and agentic AI application and development, with hands-on experience • Great communication and interpersonal skills

Preferred • Master or PhD degree in relevant field • Business stakeholder interfacing responsibility and experience • Production-grade LLM application deployment • Team management experience

#LI-Hybrid If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Compensation Overview:

Princeton - NJ - US: $167,540 - $203,013 
 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience. 

Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/.   Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include: • 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 insura

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