Data Scientist

City: Wokingham

State/Province: Wokingham

Posting Start Date: 4/14/26

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients' most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.

Job Description:

Job Description

Wipro are looking for a Data Scientist to work in Wokingham, the purpose of this role will be to deliver advanced analytics and data science capabilities to support Energy Insights & Analysis (EIA) and Future Energy Scenarios (FES) by developing scalable models, analytical pipelines and data products on NESO's Data & Analytics Platform (DAP) using Palantir Foundry. The role enables robust scenario modelling, forecasting and insight generation to inform strategic energy system decisions.

• Design, build and deploy statistical, forecasting and machine-learning models to support EIA/FES use cases
• Develop reproducible analytical pipelines and data products on DAP using Palantir Foundry (Code Workbooks, Ontology, Pipelines)
• Perform exploratory and advanced analysis on large, complex datasets (time-series, scenario, market, network and policy data)
• Translate analytical outputs into clear insights for senior stakeholders through visualisations, dashboards and narrative
• Collaborate closely with Data Engineers, Analysts, Modellers and Product Teams to align models with business and policy questions
• Ensure analytical outputs meet data quality, governance, lineage and assurance standards
• Contribute to best practices for model documentation, versioning and reuse across EIA/FES

• Strong experience in Python (pandas, numpy, scikit-learn, statsmodels) and SQL
• Applied experience in forecasting, scenario analysis, statistical modelling or machine learning
• Hands-on experience with cloud data platforms, ideally Palantir Foundry (or equivalent)
• Experience working with time-series and multi-source datasets
• Ability to explain complex analytical results to non-technical stakeholders