AI Platforms Analytics and Governance Lead

AI Platforms Analytics and Governance Lead Description - Job Summary The rapid adoption of AI platforms such as GitHub Copilot, Azure OpenAI, and enterprise AI agents has created a need for specialized expertise to monitor usage patterns, optimize consumption, control costs, and maximize business value. Traditional Data Analyst roles primarily focus on reporting and dashboarding, while traditional Data Scientist roles focus on model development and machine learning. This position combines both disciplines to provide actionable insights, predictive analytics, and cost optimization strategies for enterprise AI investments. This will provide sustainable enterprise-scale AI adoption by balancing innovation, governance, cost management, and business value realization. This role ensures use of statistical and analytical methods to explore data, identify trends, patterns, and anomalies, and extract actionable insights including model analysis, predictive analytics, and cost optimization strategies for enterprise AI investments. The role works closely with teams across the organization to understand their data needs, provide insights, and support their data-related initiatives.

Manage and optimize enterprise AI platforms including GitHub Copilot and OpenAI. Define platform standards, governance policies, and model consumption guidelines. Evaluate emerging AI technologies and recommend adoption strategies. Partner with security, legal, privacy, and compliance teams. Develop budget guardrails and cost allocation strategies. Create consumption forecasting models and executive dashboards. Identify optimization opportunities including: Prompt engineering Prompt caching Model routing Token reduction Context window optimization RAG optimization Batch processing Agent orchestration improvements Defines and creates extensive plans, data collection and analysis procedures and data insight visualizations for assigned projects. Analyzing AI platform usage, token consumption, licensing utilization, and user adoption trends. Developing forecasting models to predict AI credit consumption, budget requirements, and capacity needs. Leverages recognized domain expertise, business acumen, and experience to influence decisions of executive business leadership, development partners, and industry standards groups. Drives innovation and integration of new data science related technologies and practices into projects and activities in the business. Stays up-to-date with emerging technologies and trends in the business intelligence field, and recommends innovative solutions. Acts as a functional manager within area of expertise, developing strategy and setting functional policy and direction. Provides mentorship and guidance to lower-level employees, thus ensuring the realization of operational and strategic plans. Creating executive dashboards and KPIs to measure AI adoption, business value realization, and return on investment. Performing statistical analysis and machine learning techniques to detect anomalies, forecast spend, and recommend efficiency improvements. Partnering with platform owners, engineering teams, finance, procurement, and business stakeholders to drive data-driven decisions.

Recommended Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 10+ years of work experience, preferably in data analytics, database management, statistical analysis, or a related field. Preferred Certifications • Programming Language/s Certification (SQL, Python, or similar) Knowledge & Skills • Agile Methodology • Business Intelligence • Computer Science • Dashboard • Data Analysis • Data Management • Data Modeling • Data Quality • Data Science • Data Visualization • Data Warehousing • Extract Transform Load (ETL) • Machine Learning • Power BI • Python