Senior Manager - Data Science

Responsibilities

• Lead Data Science Projects: Design, develop, and deploy predictive and explanatory analytical solutions that address critical business problems using machine learning, NLP, and generative AI. Strengthen forecasting, refine incentive plan designs, and identify gaming behaviors
• Drive Analytics: Deliver high-impact analytics to inform strategy by developing actionable insights into Sales and client behavior. Introduce new approaches to transform complex behavioral data and influence decision-making across the organization
• GenAI Analytics Use Case Development: Lead key workstreams in the design, development, and operationalization of a GenAI-enabled analytics solution that synthesizes internal performance and external competitive signals into actionable insights, with defined success metrics, ongoing monitoring, and approaches for LLM-based feature generation on unstructured data.
• Develop Modeling Capabilities: Build and evaluate models using modern ML frameworks (e.g., TensorFlow, PyTorch), focusing on scalability, performance, and interpretability
• People Leadership: Lead a team of high-performing data scientists
• Collaborate Across Teams: Establish and maintain close relationships with key cross-functional stakeholders to understand business strategies, develop goals, and address opportunities
• Develop Scalable Solutions: Architect and deploy robust, efficient, and scalable data pipelines and modeling solutions using modern cloud and distributed compute patterns
• Lead Innovation Through External Perspective: Stay current on advancements in machine learning, deep learning, and generative AI; evaluate emerging approaches; translate theoretical advances into practical, scalable solutions that advance business outcomes. Challenge the status quo and demonstrate strong curiosity
• Define Performance Indicators: Lead analytics and measurement across key performance indicators. Own stakeholder and executive-level communications on initiative progress, including automated monthly measurement tied to specific strategic initiatives
• Communicate Insights Effectively: Present findings, recommendations, and results to both technical and non-technical audiences, including executive leadership, through clear reports, visualizations, and presentations, to enable data-driven decision-making