Principal Specialist, Data Science & Artificial Intelligence

Job description

This role leads advanced data science and analytics initiatives within the Agentic AI department. It translates business problems into scalable analytical solutions, AI-enabled insights, predictive models, and decision intelligence products. It helps build enterprise capabilities using trusted data, machine learning, automation, and agentic AI concepts to improve productivity, operational performance, and decision making. Designs and delivers predictive, prescriptive, diagnostic, and exploratory analytics solutions. Develops machine learning models, statistical analyses, simulations, optimization approaches, and ensures outputs are interpretable, actionable, repeatable, and aligned with business value and governance. Supports agentic AI use cases by defining data, model, workflow, evaluation, and decision-support requirements, collaborating with AI engineers, platform, data engineers, and stakeholders. Establishes evaluation methods for AI insights, model performance, business impact, and continuous improvement. Creates reusable analytical assets, data science patterns, and decision intelligence products, with clear documentation of assumptions, data sources, model logic, limitations, controls, and expected usage

Requirements

• Experience leading data science and analytics initiatives
• proficiency translating business problems into analytical solutions
• knowledge of developing predictive, descriptive, and diagnostic models
• proficiency developing machine learning models, statistical analyses, and simulations
• knowledge of applying automation and agentic AI concepts
• proficiency ensuring interpretability, actionability, and repeatability of outputs
• experience defining data, model, and workflow requirements for agentic AI
• proficiency collaborating with AI engineers, data engineers, and stakeholders
• knowledge of evaluating model performance and business impact
• proficiency applying data science governance, model validation, and performance monitoring
• proficiency documenting assumptions, data sources, and model logic

Skills