Analytics Leadership Development Program Summer Internship

Role Summary

Analytics Leadership Development Program Summer Internship at Takeda. The program provides hands-on experience in commercial analytics within a data-driven pharmaceutical environment, with opportunities to analyze complex datasets and communicate insights to cross-functional stakeholders.

Responsibilities

• Performs secondary, commercial market data analyses in segmentation, customer targeting, program ROI, KPIs, and ad hoc marketing analyses
• Supports market and price forecasting through secondary market data analysis
• Applies model building and coding to analyze market dynamics (e.g., resource allocation, response to marketing stimuli, customer segmentation/targeting) using optimization, regression, and Monte Carlo simulations
• Uses the scientific method to uncover business insights by formulating questions, developing hypotheses, conducting experiments, and drawing actionable conclusions for brand teams
• Conducts promotion response analysis for brand tactics to optimize ROI
• Conducts longitudinal claims analysis to identify treatment patterns and algorithms
• Prepares presentations to senior management on market planning, product selection, and changing business environment

Internship Details

• Work on business-critical projects impacting patients
• Mentorship from a Senior Commercial Leader
• Internship workshops and senior leadership speaker series
• Team-building and professional networking events

Requirements

• Master’s degree students in Data Science, Business Analytics, Marketing Analytics or related field
• Three to five years of prior work experience
• Authorized to work in the US on a permanent basis without sponsorship
• Available full-time (40 hours/week) for at least 12 weeks in summer 2026
• Graduate student with at least one year of university studies prior to internship
• Returning to university for at least one semester/quarter post-internship
• Global mindset to thrive in a diverse environment
• Excellent communication and presentation skills
• Knowledge of SAS, R, or Python; advanced Excel and Tableau skills
• Understanding of quantitative principles and handling of secondary market data sources