Director, Commercial Data Strategy

Olema Oncology•San Francisco, CA

6d•Onsite

About The Position

The Director of Commercial Data Science will play a pivotal role in Olema’s commercialization efforts, enabling strategic decision-making through advanced data analytics, predictive analytics, AI, and machine learning. Reporting to the SVP of Commercial Strategy and Operations, this role will work cross-functionally to develop a roadmap for the strategic application of data science and turn complex datasets into actionable insights that strengthen go-to-market strategies and omnichannel efforts, improve market access, and drive revenue growth. The role combines data science with an understanding of the biotech industry, commercialization, market dynamics, and physician behavior. The ideal candidate can work with large, multifaceted datasets, use statistical models, and clearly communicate findings to non-technical stakeholders. The position is based in either Olema’s San Francisco or Boston office and requires approximately 20% travel. The Director will collaborate with Insights & Analytics, Marketing, Market Access, Medical Affairs, Sales, IT, and other teams to inform commercial strategy, build and maintain analytical and predictive models, assess commercial initiatives, and improve reporting and operational efficiency.

Requirements

Bachelor’s degree in Marketing, Business, Life Sciences, or a related field.
10+ years of relevant work experience, including 8+ years in data science or advanced analytics focused on commercial applications in the biotechnology or pharmaceutical industry.
Strong understanding of biotech or pharmaceutical market dynamics, patient access, healthcare system intricacies, and regulatory requirements.
Ability to develop and implement strategic marketing initiatives using a data-driven approach and strong analytical skills.
Excellent verbal and written communication skills, including the ability to convey complex information clearly and empathetically to patients and healthcare providers.
Proven ability to work effectively across functions and lead collaborative initiatives with internal and external stakeholders.
Exceptional organizational skills and experience managing multiple projects, timelines, and priorities in a fast-paced environment.
Ability to work with large, multifaceted datasets, leverage statistical models, and communicate findings to non-technical stakeholders.
Strategic synthesis skills, including connecting disparate information and identifying insights relevant to business decisions.
Structured problem-solving skills, including framing ambiguous questions into hypotheses, workstreams, and decision pathways and applying consulting-style rigor.
Ability to collaborate across disciplines and develop strong partnerships across Commercial, Market Access, Medical Affairs, Finance, and other functions.
Comfort working in a fast-moving environment with incomplete information and evolving priorities.
High integrity, sound judgment, objectivity, rigor, and willingness to appropriately challenge strategic decisions.

Nice To Haves

Advanced degree.

Responsibilities

Work with stakeholders across Insights & Analytics, Marketing, Market Access, Medical Affairs, and Sales to understand business objectives and develop the roadmap and strategic application of data science.
Provide data-driven insights and strategic recommendations to support commercialization efforts.
Develop and maintain advanced analytical models for commercial decision-making and go-to-market strategies.
Analyze claims, sales, CRM, and marketing datasets to uncover insights and provide actionable recommendations to cross-functional teams.
Design and execute experimentation and customer behavior analysis to evaluate commercial strategies and identify opportunities to refine the commercial approach.
Apply machine learning and statistical modeling to predict trends, physician behavior, market dynamics, and sales performance.
Build and refine predictive models for local sales planning, market opportunity identification, and resource allocation.
Use advanced algorithms to optimize field team effectiveness and identify high-value customers or market segments.
Identify opportunities to leverage AI to automate work.
Create and present clear visualizations and reports to senior leadership, translating complex analyses into actionable insights and business strategies.
Provide regular updates and strategic recommendations based on data trends and performance metrics.
Develop and implement automated reporting solutions to improve operational efficiency.
Work with IT to ensure data pipelines, tools, and dashboards are efficient, scalable, and aligned with commercial needs.