Sr. Data Scientist - Advanced Analytics & AI

Over time, this role will own one of the five core predictive/prescriptive engines within the organization. Each engine will have multiple models as components. To lead the development of this engine, the role will require expert ability in mathematical modeling, analytical and heuristic solution methods, the ability to synthesize, visualize, and communicate results, and create tools at scale to drive recommended courses of action.

This role will help advance the organization's AI capabilities by applying Generative AI, LLMs, and agent-based solutions to enhance decision-making, automation, and business outcomes.

This role will require close collaboration across business functions, operating companies, specialty companies, geographies, and technology teams to align priorities and ensure the appropriate path to value. This role is expected to create models while also coaching team members in model development., * Ensure the data mined, cleansed, and engineered for models is accurate and appropriate.

• Bring forward new and diverse datasets to help solve business problems.
• Own multiple models associated with one of the organization's predictive/prescriptive engines.
• Evaluate emerging AI technologies and identify opportunities to improve model performance, automation, and business outcomes.
• Develop and integrate AI-enabled solutions leveraging Generative AI, Large Language Models (LLMs), and intelligent agents to enhance predictive and prescriptive decision-making.
• Identify and use appropriate advanced analytic tools, technologies, and platforms to solve business problems; create the roadmap for the engine, sequence models over time, develop or direct the creation of models and algorithms, and tune models to ensure desired business outcomes.
• Ensure performance scorecards and dashboards used to monitor adoption, implementation, and impact of models and strategies are effective and shared across the enterprise.
• Work cross-functionally within Enterprise Analytics and broader business teams to tune models and maximize value creation.
• Partner with Business Technology resources on APIs, front-end applications, and downstream integrations.
• Collaborate with business process owners to validate model outputs and construct appropriate training approaches.
• Work with data scientists and associate data scientists to ensure the correct data sets, calculations, and analytical methods are used to solve business problems.
• Act as a magnet for data science talent.
• Publish papers and speak at industry conferences to help attract emerging analytics and AI talent.

• Bachelor's degree + 5 years, Master's degree + 3 years, or PhD + 2 years of industry experience in management consulting, strategy, analytics, a specialized analytics company, or a corporate analytics organization.
• Familiarity with modern AI frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies.
• Understanding of AI orchestration, RAG architectures, and AI governance best practices.
• 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments.
• 2+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java).
• 3+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning, or time-series analysis.
• 7-10 years of overall analytics experience, inclusive of post-graduate work. - Experience developing and deploying Generative AI, LLM, or AI agent solutions in enterprise environments.