AI Scientist / Engineer

Position Summary We are seeking an experienced AI Scientist / Engineer – Data Science & Analytics to join a team focused on AI strategy, analytics, and value realization initiatives. This role is responsible for building enterprise AI analytics capabilities that provide visibility into AI adoption, utilization, costs, ROI, and business value. The successful candidate will design scalable data pipelines, develop executive dashboards and KPI frameworks, analyze AI usage and performance data, and translate complex datasets into actionable insights for leadership. The ideal candidate brings 5+ years of experience in Data Science, Data Analytics, Data Engineering, or AI Engineering, along with strong hands-on expertise in Python, SQL, business intelligence/visualization platforms, cloud data technologies, and enterprise AI platforms. Key Responsibilities: AI Analytics & Executive Reporting • Design and develop enterprise AI usage dashboards, executive scorecards, and analytics solutions across multiple AI platforms. • Develop KPIs and measurement frameworks for AI adoption, utilization, token consumption, credits, costs, ROI, and business value realization. • Create executive-level visualizations and reports that support strategic technology investment decisions and governance initiatives. • Translate complex technical and analytical findings into clear, actionable insights for executive leadership. Data Engineering & Integration • Build scalable data pipelines to ingest, integrate, transform, and analyze AI usage, operational, and financial data. • Integrate data from APIs, cloud platforms, data warehouses, AI platforms, and enterprise systems. • Establish reliable data models that support enterprise AI analytics and reporting. • Ensure data quality, consistency, governance, and reliability across reporting environments. Data Science & AI Measurement • Apply statistical and data science techniques to identify AI adoption trends, utilization patterns, optimization opportunities, and value realization. • Analyze AI and large language model (LLM) usage metrics, including prompts, tokens, credits, API consumption, model utilization, and associated costs. • Develop forecasting and analytical models that support portfolio planning and technology investment decisions. • Measure AI ROI and business outcomes across a variety of enterprise use cases. AI Portfolio & Value Realization • Support enterprise AI portfolio management through utilization analysis, performance monitoring, and cost optimization. • Partner with technology teams, security, finance, procurement, and business stakeholders to establish trusted enterprise AI metrics. • Recommend improvements to AI measurement frameworks, reporting standards, KPIs, and executive dashboards. • Provide data-driven insights that support AI governance and strategic technology investments. Required Qualifications: • Bachelor's degree in Computer Science, Data Science, Analytics, Engineering, or a related field; Master's degree preferred. • 5+ years of experience in Data Science, Data Analytics, Data Engineering, AI Engineering, or a related discipline. • Strong hands-on experience with SQL and Python. • Experience developing enterprise dashboards using Power BI, Tableau, or similar business intelligence platforms. • Experience building and integrating data pipelines across APIs, cloud platforms, data warehouses, and enterprise systems. • Knowledge of AI and LLM platforms and associated usage metrics, including prompts, tokens, credits, model utilization, API consumption, and cost analysis. • Experience designing executive dashboards, KPI frameworks, and performance reporting solutions. • Strong understanding of data governance, data quality, analytics, and reporting best practices. • Excellent communication skills with the ability to translate technical and analytical findings into executive-level business insights. Preferred Qualifications • Experience measuring AI adoption, ROI, utilization, and value realization within a large enterprise environment. • Experience with enterprise AI platforms and services, including cloud-based AI and generative AI solutions. • Experience with cloud data and analytics platforms such as: • Microsoft Fabric • Azure Synapse • Databricks • Snowflake • BigQuery • Similar enterprise analytics platforms • Familiarity with FinOps, AI governance, cost optimization, and technology portfolio management practices. • Experience supporting senior leadership through strategic analytics, dashboards, and performance reporting. • Experience working within large, complex, cross-functional enterprise environments. Ideal Candidate Profile The ideal candidate combines strong data engineering, analytics, and AI measurement capabilities with an understanding of enterprise AI adoption and value realization. This individual should be comfortable working hands-on with Python, SQL, APIs, cloud technologies, data pipelines, and business intelligence tools while effectively communicating insights to technical and business stakeholders. Candidates with experience building analytics solutions around Generative AI, LLM usage, token consumption, AI costs, adoption metrics, ROI measurement, and executive reporting will be particularly well aligned with this position.