US Brand Analytics Director

In this player-coach role, you will partner with Commercial, Medical, Market Access, Sales, Finance, Forecasting, and Insights to translate pressing business questions into rigorous, decision-ready analytics. You will integrate patient-level, claims, EMR, prescription, and affiliation data with research and forecasting to surface opportunities, quantify risks, and inform resource allocation.

Accountabilities

• Insight and Executive Partnership: Synthesize commercial performance into concise narratives that clarify growth drivers, risks, and trade-offs, elevating insights into action for senior leaders.
• Pre-Launch and Launch Readiness: Lead analytics for market definition, opportunity assessment, segmentation and targeting, KPI design, performance baselines, and post-launch measurement to accelerate confident decisions.
• Patient Journey Analytics: Build longitudinal patient journeys and treatment-pathway analyses to refine positioning, guide investment choices, and inform forecasting assumptions.
• Segmentation and Targeting Excellence: Lead HCP-level segmentation and optimize call plans, deploying advanced machine learning where it enhances impact and precision.
• Data Integration and Tooling: Leverage syndicated, claims, and EMR sources to generate timely insights; design centralized repositories to reduce inconsistencies and enable self-service.
• AI and GenAI Enablement: Drive adoption of AI and generative AI solutions, from automated insight generation to predictive modeling, improving speed and decision quality.
• Capability Building and Innovation: Pilot new data sources and tools with test-and-learn rigor; scale capabilities that demonstrate business value and foster responsible innovation.
• Portfolio Roadmapping: Maintain a transparent analytics roadmap, prioritizing work by strategic value, decision impact, and data readiness to ensure focus and delivery.
• Vendor and Budget Stewardship: Manage external partners and secondary data investments, aligning spend with commercial priorities and measurable outcomes.
• Team Leadership and Mentorship: Guide internal and offshore resources, contractors, and vendors; set standards for quality, timelines, and business relevance across the analytics portfolio.

Essential Skills/Experience

• 7+ years of experience applying advanced analytical methods and statistical procedures to large and disparate datasets
• Statistical analysis & modeling, including Design of Experiments, Time Series, Regression, Applied Econometrics and Bayesian methods
• Data mining, predictive modeling & machine learning algorithms
• 3+ years of recent experience and proficiency with Python, R, SQL, and big data technologies, including the Hadoop ecosystem and Cloudera distribution tools such as Impala, Hive, HBase, Spark, MapReduce
• Demonstrated pharmaceutical, biotechnology, healthcare, payer or closely related commercial analytics experience, with strong understanding of how analytics supports brand strategy, launch readiness and performance management
• Working knowledge of data visualization – MicroStrategy, Tableau, Power BI, QlikView, D3.js or similar tools
• Proficiency in Microsoft Office applications, particularly Excel and PowerPoint
• Demonstrated expertise managing, analyzing and extracting insights from large longitudinal and transactional healthcare datasets, including claims, EMR, prescription, and other patient-level data
• Quantitative bachelor's degree from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Applied Mathematics, Computer Science, or Data Science
• An advanced degree is preferred (Master's, MBA or PhD)

Desirable Skills/Experience

• Strong leadership, interpersonal, communication, and influencing skills, with demonstrated ability to collaborate effectively with senior business leaders and cross-functional partners and translate complex analyses into succinct, compelling insights and recommended actions
• Experience scaling self-service analytics, reusable data products, automation or responsibly governed AI/GenAI solutions
• Strong strategic and critical thinking, organizational discipline and the ability to operate effectively in a complex, fast-moving, and ambiguous environment