Lead, Global Advanced Analytics

Role Summary

Lead, Global Advanced Analytics, reporting to the Senior Director of Market Research and Advanced Analytics. You will support the transformation of advanced analytics for the global Oncology Business Unit (OBU), design and implement analytics solutions, and drive a data-driven future for Takeda Oncology. The role emphasizes leadership, storytelling, and fluency with GenAI to accelerate advanced analytics capabilities and inform senior leadership strategy. Location is Boston, MA.

Responsibilities

• Lead execution of long-term OBU advanced analytics strategy that integrates broader strategic goals and organizational initiatives to aid data-driven decision making and growth
• Understand key business questions in the context of the OBU vision/objectives, then develop hypothesis, design and execute key analytics to address the business questions
• Conduct above-market analytics to enable launch excellence and improve in-market performance
• Develop standardized analytics frameworks to guide regions and share best practices among insights and analytics community
• Become the change agent by driving innovation with use of latest GenAI and ML approaches to solving complex analytical problems
• Build relationships with business users of advanced analytics insights to support their requirements through effective communication, data governance and documentation
• Execute innovative use of data assets and decision sciences methods to assist other OBU teams in answering challenging questions including using latest genAI and ML approaches

Qualifications

• BA or BS degree required. Master’s degree in computer sciences, Statistics, Business, or related field preferred
• Minimum 8+ years’ related experience in commercial and advanced analytics required
• 3+ years’ experience in the bio/pharmaceutical or related field with direct responsibilities in advanced analytics, data strategy and governance required
• Demonstrated ability to translate strategy into action; excellent analytical skills and an ability to communicate complex issues in a simple way and to orchestrate plans to resolve issues and mitigate risks
• Experience working with all levels of management and consulting with key business stakeholders. An ability to influence greater outcomes
• Knowledge of advanced analytics approaches and methodologies and best practices of leveraging data to drive informative decisions
• Proficiency in using advanced analytics to drive business value including ROI/value assessment, digital KPI tracking, campaign measurement, etc
• Experience leveraging complex data to drive business decisions, hands-on experience in data science methodologies (predictive analytics, machine learning, patient-level data triggers) using R, Python, SAS in Databricks; deep knowledge of Qlik, PowerBI, Tableau for visualization; fluency with pharma data sources such as Veeva and IQVIA including RWD sources (TriNetX, Flatiron, Optum, Komodo)
• Deep knowledge of statistical tools and ability to code to design and execute complex advanced analytics
• Able to set priorities, manage multiple projects and timelines simultaneously
• Ability to build strong relationships with internal and external stakeholders
• Ability to manage vendor relationships and maintain an accurate budget
• Data-driven mindset; making decisions based on sound analytics and continuous study of data
• Driven to quickly arrive at answers to deliver on results
• Excellent communication of ideas, including written and in-person presentation skills; ability to communicate changes with transparency to all stakeholders
• Ability to quickly learn Oncology therapeutic area and products
• Travel requirement: 10%, more as needed for specific business purposes, some international travel may be required

Skills

• Knowledge of advanced analytics approaches and methodologies and best practices for leveraging data to drive informative decisions
• Proficiency in driving business value with advanced analytics including ROI/value assessment, digital KPI tracking, and campaign measurement
• Hands-on experience in data science methodologies (predictive analytics, machine learning, patient-level data triggers) using R, Python, SAS in Databricks; visualization with Qlik, PowerBI, Tableau; familiarity with pharma data sources such as Veeva and IQVIA; RWD sources such as TriNetX, Flatiron, Optum, Komodo
• Strong statistical tool knowledge and coding ability to design and execute complex analytics
• Strong project management and stakeholder collaboration capabilities

Additional Requirements

• Travel: 10%, more as needed for specific business purposes; some international travel may be required