AI/ ML Engineer

Job description

**Key Responsibilities** Drive execution of the Enterprise Portfolio Insights \& Governance strategy to deliver measurable business outcomes, accelerate decision-making, and enable speed and flow of delivery across the portfolio Lead development and prioritization of the Enterprise Portfolio Data Insights \& Governance reporting \& analytics roadmap, ensuring alignment across stakeholders and user personasImplement and maintain a robust governance framework for enterprise portfolio data to maintain hygiene, ensure accuracy, and uphold trust in insights, enabling reliable analytics and reporting at scaleAutomate manual and repetitive tasks, including presentations and analytical workflows, to improve efficiency and scalability across TBE, LOBs, Product, and TechnologyAdvance integration of AI, ML, BI, and emerging technologies, by delivering practical use cases and promoting industry best practices to mature analytics capabilitiesTranslate complex data into compelling narratives and actionable insights, crafting recommendations that inform and influence senior leader decision-makingDemonstrate ability to self-start, carving opportunities out of white space and driving results with a high degree of independenceExcel in a fast-paced environment, adjusting to shifting priorities while maintaining focus on quality and outcomes **Required Skills \& Qualifications** Minimum of 5 years of progressive experience in Data Analytics/Data Science, product development, and engineering teams, with a proven track record of delivering complex, cross-functional initiatives Bachelor's Degree or higher in business, economics, statistics, mathematics, engineering, or a related field Expertise in Python, Power BI, Tableau, AI/ML, custom GPTs, data modeling, and advanced Excel, with hands-on experience applying analytics to business and portfolio decisioning Experience working with large language models (e.g., Llama, OpenAI GPT) and applying techniques such as retrieval-augmented generation (RAG) and vectorization to analytics or decision-support use cases; familiarity with agentic AI and Graph RAG concepts is a plusAdvanced user of enterprise collaboration and reporting tools including Jira, Rally, Clarity, Apptio Target Process, Confluence, Tableau, Power BI and AirtableDemonstrated success in managing large, complex products or portfolios with multiple stakeholders across product, technology, and business teamsHighly skilled in Agile product development methodologies, program and project management, with experience contributing to and executing against a product or analytics roadmap Exceptional collaboration and thought leadership skills, with a proven track record of partnering effectively across global teams to solve complex problemsStrong strategic and analytical orientation, combining numerical proficiency with forecasting capabilities and financial acumen to drive business insights and recommendations Excellent executive communication skills with the ability to capture and translate insights into a clear story and recommendations to senior audiences