AI Data Analyst

AI Data Analyst Whitehall Resources currently require an experienced Data Analyst to work with a key client based in Cambridge **Please note this role requires 2 days onsite weekly and falls INSIDE IR35** Job Overview This role is a critical enabler of enterprise AI transformation, supporting the data and reporting capabilities needed to measure, manage, and accelerate AI adoption across the business. Working across AI Enablement, Data, IT, Finance, and other enabling functions, the role will bring together and analyse data from multiple systems, support day-to-day reporting, and contribute to the stewardship of AI-related datasets. This role will help ensure AI-related data is accurate, accessible, appropriately governed, and translated into reliable dashboards, reports, and operational insights. Responsibilities • Produce monthly, quarterly, and ad hoc reporting with the AI Senior Analyst, covering AI adoption, engagement, productivity, ROI, and business impact. • Operate effectively in a fast-paced and evolving environment, managing ambiguity and changing priorities. • Analyse and combine data from multiple systems to generate reliable insights and reporting. • Manage recurring data activities, including collection, validation, reconciliation, refreshes, and issue resolution. • Work with Data, IT, and business stakeholders to improve data quality, definitions, documentation, ownership, and access. Required Skills and Experience • Experience using Databricks for data analysis, transformation, machine-learning workflows, and automation. • Strong proficiency in SQL and experience working with structured and unstructured data from multiple systems. • Experience using Python, notebooks, or similar scripting tools for data preparation, analysis, or automation. • Experience with Power BI, Excel, Tableau or equivalent BI tools, including data modelling and visualisation. • Understanding of data governance, metadata, lineage, and access-control principles. • Experience interpreting data and communicating findings to technical and non-technical stakeholders. • Ability to investigate data issues and support root-cause analysis. • Strong attention to detail, documentation, and process control. • Skilled in using AI and automation tools such as ChatGPT, Codex, Microsoft Copilot, GitHub or Power Automate. • Understanding of AI token usage, consumption patterns, associated cost drivers, and the wider AI technology landscape. Nice-to-Have Skills and Experience • Knowledge of machine-learning workflows, agent-development toolkits, and large-scale data-processing concepts. • Familiarity with Azure Data Lake, Unity Catalog, Delta Lake, or related data-platform capabilities. • Experience supporting advanced analytics dashboards, process-intelligence solutions, or automated measurement solutions. • Awareness of CI/CD, version control, and deployment practices used in data and analytics environments.