Business Analyst, Sr.

Role Summary

Senior Pricing Analyst within BioLife Forecasting, Pricing & Analytics (FPA) at Takeda, leading end-to-end analyses to influence pricing strategies and drive business growth through advanced data analytics, statistical modeling, and machine learning. Reporting to the Associate Director, Pricing, and Business AI Lead. Focus on delivering actionable insights and recommendations to senior leadership.

Responsibilities

• Leverage advanced analytical techniques to connect raw data across multiple sources, identify trends, and generate insights that inform business decisions.
• Assess pricing performance, identify key drivers, risks, and opportunities across different centers, fee levels, and donor segments.
• Contribute to pricing and forecasting projects through statistical analysis, automation, and experimentation, including A/B testing.
• Develop and implement machine learning models to enhance plasma donor insights, optimize pricing strategies, and improve operational efficiency.
• Own the experimentation lifecycle, from designing experiments to analyzing results and scaling successful initiatives.
• Set best practices in analytics, data storytelling, and code quality to elevate team capabilities and ensure consistency.
• Collaborate with cross-functional teams and senior leadership to translate complex data findings into strategic recommendations.
• Continuously seek new opportunities for data-driven improvements and support the implementation of innovative solutions.

Qualifications

• Required: Bachelor‚Äôs degree in Economics, Statistics, Computer Science, Engineering, Data Science, or related quantitative field; Master‚Äôs degree preferred.
• Required: Minimum of 5+ years of experience in analytics, pricing, strategy, or forecasting with demonstrated impact.
• Required: Proficiency in statistical analysis, experimental design, regression analysis, causal inference, and hypothesis testing.
• Required: Hands-on experience with PySpark, Python, SQL, and BI tools (Power BI or Tableau).
• Required: Advanced Excel skills for rapid data analysis and visualization.
• Required: Strong analytical and quantitative skills to connect data sources, uncover patterns, and generate insights.
• Required: Excellent communication skills to translate technical findings into clear business narratives.
• Required: Experience with machine learning models (supervised/unsupervised learning, predictive retention, segmentation, elasticity modeling).
• Required: Proven ability to lead experimentation lifecycle from design to analysis and scaling successful strategies.
• Required: Ability to thrive in fast-paced, ambiguous environments with a proactive and adaptable mindset.

Skills

• Data analysis
• Statistical modeling
• Machine learning
• Data storytelling
• Experimentation design and analysis
• Cross-functional collaboration

Education

• Bachelor‚Äôs degree in a quantitative field; Master‚Äôs preferred.