Principal (Senior Director), Commercial Enterprise AI Product Mgmt., Field Force Effectiveness
Business Introduction
Responsibilities
Hunt for high-value AI opportunities
across the field force effectiveness lifecycle - rep coaching and enablement, omnichannel orchestration, and field analytics - and develop a global portfolio of AI products ranked by impact, feasibility, and time-to-value.
- Quantify value rigorously by building business cases that hold up with finance and executive sponsors - cycle time saved, decisions accelerated, revenue uplift, cost avoided, scientific productivity gained.
•
Develop domain pattern recognition
Own the Enterprise AI opportunity portfolio,
Make hard trade-off calls —
Say no, with evidence,
Be the strategic counterpart to the forward deployed, full-stack, and data engineering leads,
translating ambiguous business problems into crisp problem statements, prototypes, success metrics, and decision frameworks engineers can build against.
- Shape engagements end-to-end - defining scope, success criteria, exit conditions, and scaling pathways before kick-off, then staying close as engineers execute.
•
Surface re-use and platform leverage,
Design the human-digital split,
Operate fluently with senior business and scientific leaders,
Build sponsor coalitions,
Communicate impact clearly,
Define how we keep score,
establishing the value-realization framework Enterprise AI uses to measure impact across deployments.
- Run honest post-mortems - capturing what worked, what didn't, and feeding those learnings back into opportunity selection and engagement design.
•
Continuously sharpen the investment thesis
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals
- 15 or more years of professional experience across some combination of pharma/life sciences, AI/ML product strategy, and product management or strategy roles in technology-led organizations.
- Experience taking at least one technology or AI initiative from problem framing through executive funding and into delivery.
- Prior responsibility with pharma field force operations, including rep coaching and enablement, omnichannel orchestration, or field analytics.
- Track record with modern AI/ML concepts - including LLMs, agentic systems, and digital workers, the ML lifecycle, and data and evaluation patterns - demonstrated through hands-on prototyping.
- Experience operating as an individual contributor without direct reports, influencing engineering and business teams through frameworks and documented decision criteria.
- Experience in product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.
- Regular use of field deployment processes, including customer/HCP segmentation, territory alignment, or call plan execution.
- Experience with field analytics and SFE KPI automation, including identifying execution gaps and producing actionable recommendations for the field.
- Proficiency using account planning or CRM systems, such as Veeva or Salesforce, to execute and track field plans.
- Experience partnering with sales leadership and brand teams to translate field performance data into targeting or resourcing decisions.
- Working knowledge of MLR and GxP compliance requirements applicable to field-facing recommendations and digital tools.
Preferred Qualifications
If you have the following characteristics, it would be a plus
- Prior experience in a forward deployed engineering, applied AI, or AI lab/COE role at a pharma, healthcare, or comparable regulated enterprise.
- Background in management consulting, value engineering, or corporate strategy with hands-on technology experience.
- Experience navigating GxP, regulatory, and data-governance requirements in pharma AI deployments.
- Experience with CRM, content, and data platforms used in field operations, such as Veeva CRM/Vault, Salesforce, IQVIA/Komodo data, or omnichannel engagement platforms.
#GSK-LI
Skills
AI Platforms, Change Management, Data Analysis, Feature Prioritization, Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis
- If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $195,525 to $325,875. • If you are based in another US location, the annual base salary range is $177,750 to $296,250. The US salary ranges take into account a number of factors including work location within the US market, the candidate's skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Uniting science, technology and talent to get ahead of disease together.
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Not included in the source posting: about the role, benefits.
Skills
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