Brand Analytics Director

The Director continuously measures performance against strategy, forecast and key business objectives, diagnoses the drivers behind results, and proactively identifies emerging opportunities, risks, unmet needs and growth levers before they become obvious in topline reporting. As a standing strategic advisor to Brand Leadership Teams, the Director brings an independent, evidence-based point of view to major business choices, challenges assumptions, connects signals across research, secondary data, competitive intelligence and forecasting, and converts analytics into clear recommendations and actions.

This is a hands-on analytical role and a proactive internal consultant to the brand team. The Director sets the analytics agenda, ensures leaders have the right KPIs and decision-support tools, and advances scalable analytics, AI and automation capabilities that improve the speed and quality of commercial decisions. The role partners closely with the Senior Director, Insights, Analytics & Forecasting. It has no direct reports but may manage contractors and consultants to complete analytical projects.

Key Responsibilities

• Develop a deep understanding of internal customers’ data and analytical needs, with a focus on customer-facing model leadership.
• Design and implement analytical solutions for business opportunities, customer segmentation and targeting, HCP and patient opportunity identification, return-on-investment analytics, optimal resource and budget allocation across Sales and Marketing channels, patient and prospective analytics, smart business experiments (test and learn), and market simulation and patient flow modelling.
• Coordinate the procurement of syndicated and custom, primary and secondary datasets.
• Champion the use of local customer insight in strategic and resourcing decisions across the business.
• Collaborate with Commercial, Sales Force Operations and Market Access teams on key business processes and joint initiatives.
• Identify and prioritize enhancements and new analytic capabilities, and lead their development, deployment and embedding across the organization, including AI and automation use cases.
• Instill a culture of continuous improvement, testing and deployment of new capabilities, and develop innovative analytical practices that sustain competitive advantage.
• Summarize and present findings through various communication channels, with clear implications and recommended actions for senior leaders.
• Apply deep technical knowledge shared across the functional area, such as key datasets and modelling capabilities, and understand how this work integrates with that of colleagues.
• Monitor the external environment for leading analytic capabilities, inside and outside pharma, that can be applied within the organization.

AI and Automation

• Embed AI into day-to-day analytics, using tools such as Databricks Genie, Genie Code and Copilot to accelerate analytical code development, model building and deliverable creation.
• Build and scale AI-enabled analytics, for example AI-assisted HCP segmentation and scoring, and AI-drafted weekly performance narratives (launch performance copilots) that analysts validate, interpret and turn into recommended actions.
• Define repeatable, governed AI use cases with measurable time and quality benefits, and partner with Data and Digital, Data Engineering and enterprise AI teams on governed data feeds and automation.
• Apply responsible AI practices: validate AI outputs, document model logic and keep human review of insights and recommendations before they reach business leaders.