Associate Director, Brand Analytics
Based in the United StatesFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonSQLMicrosoft Power BIR
Requirements
- Bachelor’s or Master’s degree in Business, Economics, Statistics, Data Science, Marketing, or a related analytical field (advanced degree preferred).
- 8+ years of experience in brand analytics, commercial analytics, business insights, or related roles, ideally within pharmaceutical, biotech, or healthcare environments.
- Strong experience supporting product launches or pre-launch strategy in complex, matrixed organizations.
- Hands-on expertise in advanced analytics and modeling techniques such as segmentation, predictive modeling, and campaign effectiveness analysis.
- Advanced proficiency in SQL and Python or R, with strong capabilities in Excel and PowerPoint.
- Experience with data visualization and analytics tools such as Power BI, Alteryx, or Dataiku is highly preferred.
- Strong communication skills with the ability to influence stakeholders and present insights clearly to executive audiences.
- Demonstrated ability to manage multiple projects and deliver high-quality analytical outputs in fast-paced environments.
Responsibilities
- Act as a strategic analytics partner to brand teams supporting launch planning, execution, and ongoing performance management for oncology assets.
- Own and evolve customer segmentation strategies, ensuring alignment with brand objectives and effective targeting across customer groups.
- Lead advanced analytics using secondary data to generate insights on market dynamics, customer behavior, patient journeys, and brand performance.
- Develop and execute predictive and prescriptive modeling approaches, including look-alike modeling and campaign effectiveness measurement.
- Design and maintain performance dashboards, KPIs, and launch measurement frameworks to track progress against business objectives.
- Partner across Forecasting, Market Research, Data Science, Medical, and Commercial teams to integrate data sources into cohesive insights and recommendations.
- Translate complex analytical outputs into clear, actionable recommendations that influence brand strategy and decision-making at the leadership level.
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