Lead Data Scientist

Kforce is seeking a Lead Data Scientist that will play a critical role in leveraging advanced analytics, data science, and modern technology to support revenue growth initiatives across multiple digital and operational channels. This position focuses on building scalable analytics solutions, developing predictive models, and implementing automation across reporting and analytical processes. Summary: This role partners closely with cross-functional business, technology, and data teams to modernize data infrastructure, enhance analytical capabilities, and deliver actionable insights to senior leadership. The position also supports the development of new data assets and dashboards as enterprise systems and platforms evolve.Lead the design, development, and deployment of advanced analytics and machine learning models to forecast revenue, optimize pricing strategies, and improve inventory performance across key revenue channels Responsibilities:

• Collaborate with technology and data engineering teams to support data platform modernization initiatives, ensuring alignment with business requirements, data integrity, and scalable architecture
• Develop and maintain executive-level dashboards and reporting solutions to replace legacy reporting processes
• Engineer and support robust data pipelines using modern ETL tools and cloud-based platforms to enable real-time and batch analytics
• Design new analytical data objects and dashboards to support newly implemented enterprise systems
• Provide analytical support for pricing, inventory, and promotional initiatives across multiple digital platforms
• Partner with business teams to deliver data-driven insights and clearly communicate complex analytical findings to non-technical stakeholders
• Ensure strong data quality, governance, and security standards across all analytics and reporting activities
• Bachelor's degree in a quantitative, technical, or business-related field required; advanced degree (MBA or MS) preferred
• Equivalent combination of education and relevant professional experience considered
• Experience with revenue management, pricing, inventory optimization, or financial analytics strongly preferred
• Industry experience in complex, transaction-based, or consumer-facing environments preferred
• Proficiency with Microsoft Office tools (Excel, PowerPoint, Word) and strong analytical skills required
• Expert-level experience with SQL, Python, Power BI, VBA, and analytics automation tools required
• Experience with enterprise analytics platforms, statistical tools, or database management systems preferred