Associate Director - US Predictive Customer Engagement

Career Areas Career Stories Join Talent Community Candidate Login English English Italiano Español Français Português Norsk Deutsch 日本語 Bahasa melayu 中文 (简体) 中文 (繁體) 한국어 ภาษาไทย Nederlands Polski Yкраїнська Hrvatski Ελληνικά Magyar čeština Türkçe Pусский Haitian עברית Brazilian Português Dansk Suomi Svenska Français (Canada) Português (Portugal) Careers Home Life at BMS Career Areas Student Opportunities Events How We Recruit Career Stories Search this site Join Talent Community Candidate Login English English Italiano Español Français Português Norsk Deutsch 日本語 Bahasa melayu 中文 (简体) 中文 (繁體) 한국어 ภาษาไทย Nederlands Polski Yкраїнська Hrvatski Ελληνικά Magyar čeština Türkçe Pусский Haitian עברית Brazilian Português Dansk Suomi Svenska Français (Canada) Português (Portugal) Single PositionView All JobsAssociate Director - US Predictive Customer EngagementPrinceton - NJ - US No longer accepting applications.Job IDR1602558Date posted06/24/2026DepartmentNot ApplicableDescription: 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 LeadershipOwn 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 FoundationOversee 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 ExcellenceLead 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 AIEnsure 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 LeadershipServe 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 DevelopmentCoach and develop engineers/data scientists; set technical standards; create a culture of operational excellence, high-quality documentation, and continuous improvement.QualificationsRequired:BA/BS degree...