Job Description - Data Analyst


Data Analyst – EIA/FES (DAP & Palantir Foundry)

Role Purpose

Support Energy Insights & Analysis (EIA) and Future Energy Scenarios (FES) by delivering high‑quality analysis, dashboards and data products on NESO’s Data & Analytics Platform (DAP) using Palantir Foundry. The role focuses on transforming complex energy system data into trusted insights that inform modelling, scenario development and strategic decision‑making.

Key Responsibilities



  • Perform exploratory and structured analysis on large, complex datasets (time‑series, scenario, market, network and policy data)

  • Support EIA/FES modelling teams by preparing, validating and analysing input and output datasets

  • Develop reproducible analysis workflows using SQL and Python within Foundry

  • Produce clear, well‑structured insight packs, visualisations and narratives for senior and non‑technical stakeholders

  • Work closely with Data Scientists, Data Engineers and Modellers to align analysis with business and policy questions

  • Ensure data outputs meet quality, governance, lineage and assurance requirements

  • Contribute to continuous improvement of analytical standards, templates and reusable assets across EIA/FES

Essential Skills & Experience



  • Strong experience in SQL and data analysis using Python

  • Experience analysing time‑series and multi‑source datasets

  • Strong data visualisation and storytelling skills

  • Ability to explain analytical findings clearly to non‑technical audiences

Desirable



  • Experience in energy systems, utilities, infrastructure or public‑sector analytics

  • Familiarity with scenario analysis, modelling outputs or forecasting concepts

  • Experience working in assurance‑led or regulated environments

  • Understanding of DAP and Foundry concepts (data products, lineage, governed analytics)

Ways of Working



  • Agile, collaborative delivery

  • Strong partnership with modelling, policy and digital teams

  • Focus on accuracy, transparency and reusability

 







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