Senior Data Scientist - Operations & Analytics
Kforce has a client in Phoenix, AZ that is seeking a Senior Data Scientist - Operations & Analytics. Summary: This is not a -heads-down- data science role-this is a leadership seat at the table. As a Senior Data Scientist, you'll drive high-impact analytics and machine learning initiatives that directly influence operational strategy and execution. You'll work end-to-end: from problem framing and data discovery to production deployment and performance measurement-while mentoring a growing team of data scientists. You'll tackle real-world, complex problems using a powerful blend of GenAI, predictive modeling, and optimization, translating advanced analytics into clear, actionable business outcomes. This role is ideal for someone who enjoys owning outcomes, influencing strategy, and building scalable analytics solutions that actually get used. Responsibilities include:
- Lead and deliver advanced data science initiatives across forecasting, optimization, experimentation, and machine learning
- Build and deploy production-ready models (statistical, ML, and AI) in cloud environments
- Perform time-series analysis, demand forecasting, hypothesis testing, and causal inference
- Design and analyze experiments to drive measurable operational improvements
- Transform large, complex datasets into actionable insights and executive-level recommendations
- Partner with business leaders to define and execute a data science roadmap
- Translate advanced analytics and AI concepts for non-technical audiences
- Mentor and elevate data scientists through best practices in modeling, experimentation, and analytics engineering
- Identify new, innovative ways to leverage enterprise data for competitive advantage
- Bachelor's degree in a STEM field (Industrial Engineering, Computer Science, Mathematics, Statistics, Engineering)
- Master's degree preferred
- 5+ years of data science experience, with demonstrated leadership or mentorship responsibilities
- Seasoned data science leader with depth, versatility, and strong business instincts
- Strong hands-on expertise in forecasting and demand modeling
- Advanced proficiency in Python or R, SQL, and cloud-based analytics environments (AWS or similar)
- Experience deploying machine learning or AI models into production
- Strong background in statistical modeling (regression, clustering, decision trees, experimentation, time series)
- Generative AI
- Traditional statistics & machine learning
- Operations Research/Optimization
- Logistics, supply chain, fleet, trucking, or distribution analytics
- Optimization use cases such as routing, pricing, maintenance, or resource planning
- Experience working closely with senior business stakeholders
- Hybrid role based in Phoenix, AZ (4 days onsite per week)
- Hiring decision contingent on completion of onsite process
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