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Summary
This person will help design, scale, and operate BMS's agentic omnichannel orchestration and next‑best‑engagement engine as a core enterprise platform. This role operates at the intersection of data science, machine learning engineering, and commercial execution, translating brand and Therapeutic Area strategies into operational decision logic, ML‑powered recommendations, and closed‑loop automation that guide actions, content, and channel selection at the individual customer level (N=1). Serving as a key delegate to the Director, Omnichannel Engine Business Product Owner, the Associate Director collaborates closely with data scientists, ML engineers, and platform teams to define the decisioning and automation roadmap, support model design and deployment, and ensure agentic workflows are integrated with CRM, marketing automation, and measurement systems. This role also plays an important part in ensuring model interpretability, governance, and continuous learning across Oncology, Cardiovascular, Neurology, and other portfolios.
Responsibilities
Agentic Omnichannel Engine Product Strategy
- Support ownership of the product vision and technical roadmap for the omnichannel orchestration and next‑best‑engagement engine, with emphasis on agentic decisioning and ML‑driven automation.
- Translate commercialization priorities and Therapeutic Area strategies into decisioning capabilities, inference patterns, and orchestration models.
- Continuously evolve the roadmap based on model performance, learning velocity, adoption, and advances in agentic AI.
Design of Agentic Decisioning & Machine Learning Logic
- Work hands‑on with data scientists and ML engineers to design and operationalize predictive, uplift, response, and recommendation models.
- Develop agent‑based decision flows and hierarchical prioritization logic.
- Define optimization objectives, constraints, and guardrails embedded into inference.
- Define model input requirements, feature availability, refresh cadence, inference latency targets, and fallback logic.
- Ensure ML outputs are translated into auditable, and actionable recommendations consumable by field and digital channels.
Translation of Brand Strategy into Engine Logic
- Partner with Brand and Therapeutic Area teams to convert customer strategies into formalized business rules, triggers, eligibility logic, and prioritization schemas.
- Encode channel‑specific nuances across field, digital, patient, medical, and access contexts.
- Balance rules‑based logic and probabilistic models to ensure performance, explainability, and compliance.
Orchestration Workflow & Automation Design
- Define and maintain agentic orchestration workflows governing recommendation generation, prioritization, and delivery.
- Partner with CRM and Marketing Automation engineering teams to enable low‑latency, scalable execution across Salesforce, Veeva, and related platforms.
- Implement champion‑challenger frameworks, A/B testing, and continuous experimentation within orchestration logic.
Closed‑Loop Learning & Measurement Integration
- Architect closed‑loop feedback mechanisms linking recommendations issued, actions executed, and customer responses.
- Partner with Business Insights, Measurement, and Data Engineering teams to define telemetry, diagnostics, and performance KPIs such as adoption, decision quality, and incremental lift.
- Apply learnings to continuously tune models, features, thresholds, and orchestration rules.
- Support incorporation of structured and select unstructured field and medical data, aligned with governance standards.
- Advocate for data quality, schema consistency, latency SLAs, and versioned metadata as foundational requirements.
- Enable API‑based, modular architecture that supports experimentation and scalable evolution.
Team, Vendor & Delivery Leadership
- Lead or coordinate portions of cross‑functional squads (data science, engineering, analytics, vendors) supporting engine build and operations.
- Support delivery planning, vendor oversight, budgeting, and quality assurance for engine‑related initiatives.
Qualifications
- Bachelor's degree in Analytics, Computer Science, Engineering, Data Science, or related field (Master's preferred).
- Minimum 5 years experience in life sciences or regulated commercial environments, with 3+ years in omnichannel orchestration, decisioning engines, ML products, or analytics platforms.
- Proven experience working directly with data scientists and ML engineers on model design, deployment, and lifecycle management.
- Strong understanding of machine‑learning systems, including predictive and prescriptive modeling, recommendation systems, uplift and causal methods, feature engineering and operationalization.
- Familiarity with agentic AI concepts, including autonomous decisioning, tool/function calling, and multi‑step reasoning workflows.
- Proficiency in Python or R, SQL, and ML libraries; experience with cloud analytics platforms such as Databricks, Snowflake, Azure.
- Experience leveraging large language models (LLMs) as reasoning or enablement layers, including embeddings and vector search, prompt‑based classification and summarization, and tool or function calling connecting models and workflows.
- Strong ability to validate AI‑generated insights for explainability, robustness, and regulatory trust.
- Solid understanding of pharmaceutical data domains, CRM platforms (e.g., Salesforce, Veeva), and digital engagement tooling.
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
Benefit Offerings
- 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
- Paid Time Off: US Exempt Employees flexible time off (unlimited, with manager approval, 11 paid national holidays). Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non‑Exempt, Hourly Employees receive 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays.
- Additional 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.
On‑site Protocol
BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site‑essential, site‑by‑design, field‑based and remote‑by‑design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role. Site‑essential roles require 100% of shifts onsite at your assigned facility. Site‑by‑design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field‑based and remote‑by‑design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
Supporting People With Disabilities
BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
Data Protection
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
Job ID: R – Associate Director, NPP Orchestration
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