Insights Analyst
Lorien
Charing Cross, United Kingdom
yesterday
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
£ 156KJob location
Remote
Charing Cross, United Kingdom
Tech stack
Data analysis
Azure
Data Infrastructure
Python
Microsoft Fabric
Job description
This role focuses on turning complex data into clear, decision-ready insight. The Insights Analyst will work closely with business stakeholders to frame the right questions, deliver robust statistical analysis, and translate outcomes into actionable recommendations. They will also partner closely with an Analytics Engineer to ensure insights are supported by scalable, reusable data products within a modern data platform (Microsoft Fabric).
What the Insights Analyst will be doing:
- Engaging stakeholders to translate business goals into well-defined analytical problems
- Performing statistical analysis and modelling using Python and/or R (eg regression, time series, segmentation, driver analysis)
- Applying strong analytical discipline: validation, interpretability, and clear documentation
- Communicating insights through clear narratives, highlighting implications, trade-offs, and uncertainty
- Working with the Analytics Engineer to ensure outputs become reusable features, metrics, and datasets
- Collaborating with federated analysts to drive consistent approaches and adoption
- Operating in an agile environment with a focus on fast, high-quality time-to-insight
Requirements
- Experience with forecasting, attribution, inventory/supply analytics, or driver analysis
- Hands-on experience with Python and/or R for applied analytics
- Proven background delivering statistical analysis and/or ML in a commercial setting
- Excellent stakeholder management and problem-framing skills
- Ability to work closely with data and analytics engineering teams on data requirements and quality
- Experience across commercial, supply chain, or manufacturing analytics
- Experience with modern data platforms and notebook-based workflows (Fabric preferred) as well as Azure and Dataflows.