Partner - AI & Analytics

What You'll Own & Deliver

AI Strategy and Prioritization: Define and maintain a unified AI strategy across three lanes: internal workflow and operations, consulting engagements, and product development. Set clear priorities and decision-making frameworks, and create the boundaries that give individual teams room to build while keeping the broader organization pointed in the same direction. 

Cross-Functional Coordination: You will be the connective tissue between AI innovation, consulting, and product -- driving alignment on goals, sequencing investments, and resolving the tensions that come with fast-moving capability building across multiple teams. Note that overall product roadmap ownership sits elsewhere; this role is responsible for ensuring AI priorities are well-represented, coordinated, and sequenced within that broader roadmap process. 

Expert Partner to Account Leaders: You will serve as a deep resource to our account leaders in client conversations. That means being able to take a conversation 2 to 3 engagements deep on method choices, tradeoffs, and risk -- and being as comfortable telling a client where AI is not the right answer as where it is. You bring your relationships and network to support broader Beghou growth, but independent pipeline ownership is not the primary expectation of this role. 

Business Metrics and Investment Oversight: Own the business case for AI investments. That includes build cost assumptions, ROI frameworks, and tracking time and revenue return against projections. You will bring the same rigor to AI investment decisions that we bring to client engagements. 

GTM and Narrative: Set the AI communication narrative and go-to-market positioning, aligned to Beghou's overall GTM strategy. This includes defining our thought leadership agenda in service of business priorities. 

Team and Delivery Model: Define how we staff and deliver against custom AI and analytics projects, including the right balance of domain and commercialization expertise versus AI technical depth. You will work with and develop existing teams, which means your ability to assess, shape, and redeploy talent matters as much as your ability to hire. 

AI Upskilling and Change Management Own a centralized point of view on what our people need to work effectively in an AI-enabled environment -- across consulting, product, and internal teams. That means assessing current capability gaps, defining what good looks like at different levels of the organization, and being accountable for pulling that agenda through in partnership with people operations and training. You are not doing this alone, but are the one making sure it happens and that it stays connected to where our AI strategy is actually going. 

What You Bring

Applied AI fluency. You can hold a substantive conversation about model choices, methodology tradeoffs, and risk without a technical translator in the room. You can engage directly with AI experts, ask the right questions, and evaluate outputs for business applicability and relevance. You do not need to build models or agent systems, but you need to know when a result is wrong for the problem. 

Deep pharma commercial instincts. The ability to assess an AI output -- a patient segmentation, an SFE model, an omnichannel recommendation -- and determine whether it reflects how the market actually works.  

Organizational leadership. Proven ability to lead across functions, with and without direct authority. You know how to set direction, build trust, and keep teams aligned when priorities are competing. 

Business orientation. You think in terms of return, prioritization, and tradeoffs. You are as comfortable in a conversation about investment decisions and build costs as you are in a conversation about solution design. 

Communication. You translate complex ideas without losing the complexity that matters -- in client conversations, internal team settings, and executive discussions. 

Continuous learning and market awareness. The AI landscape is moving fast and this role requires someone who is genuinely invested in keeping pace with it. That means actively monitoring new capabilities, testing and evaluating emerging tools and models, and integrating what you learn into how we make decisions and how we show up with clients. Credibility at the client interface depends on being current, not just experienced. 

Qualifications 

17+ years of experience spanning life sciences and AI or advanced analytics, with meaningful time in a consulting or advisory context 

Demonstrated experience leading or overseeing AI-driven projects in pharma commercial settings, with the ability to speak to what worked, what didn't, and why 

Familiarity with modern AI/ML approaches (LLMs, generative AI, machine learning, agentic systems) at the level of an informed strategic decision-maker 

Practical understanding of commercial AI systems in life sciences -- not just familiarity with tools, but experience with how these systems are designed, deployed, and evaluated in real commercial contexts 

Track record of cross-functional leadership and organizational alignment in complex, fast-moving environments 

Experience owning or contributing to business development in a professional services or consulting context 

Demonstrated habit of staying current -- actively testing new tools, following capability developments, and translating what's new into what's relevant for the business and for clients 

• Advanced degree in a relevant field (Data Science, Engineering, Life Sciences, Business, or equivalent experience)