Senior Data Scientist

Your New Role

We're looking for a Senior Data Scientist to lead the development and application of advanced analytics and machine learning techniques that answer complex business questions and drive strategic decisions. You'll work closely with data engineering and business teams to design models and analytical solutions that improve customer experience, optimise operations, and support financial and strategic planning.This role combines technical expertise with leadership responsibilities, including mentoring analysts and engineers, translating insights into actionable recommendations, and ensuring data science practices align with organisational goals.

Key Responsibilities
Customer Insights: Build churn prediction models, apply clustering and segmentation, and use NLP for sentiment analysis to improve service quality and retention strategies.
Operational Performance: Develop forecasting models for network demand, implement anomaly detection for outages and latency, and create predictive maintenance solutions to reduce downtime.
Efficiency & Planning: Optimise field operations through predictive scheduling and route planning, support inventory forecasting, and identify fraudulent or abusive usage patterns using ML techniques.
Financial & Strategic Analysis: Deliver cost-to-serve models, profitability analysis, and scenario modelling to guide investment and regulatory decisions.
Geospatial Analytics: Apply spatial modelling and visualisation techniques to support network planning, operational assessments, and customer analysis.
Data Science Leadership: Mentor team members, present insights clearly to technical and non-technical audiences, and ensure best practices in analytical workflows.
Technical Delivery: Engineer and optimise analytical and spatial SQL, build feature enrichment pipelines, develop and evaluate ML models, and package outputs for deployment.
What You'll Need to Succeed
Strong experience in applied machine learning (regression, tree ensembles, experiment design).
Advanced proficiency in Python and SQL, with experience in spatial SQL and PostGIS.
Familiarity with spatial tools and libraries (GeoPandas, QGIS) and feature engineering concepts.
Experience with data modelling, dbt, and version control (Git).
Knowledge of spatial datasets (MasterMap, AddressBase, Land Registry).
Desired: Experience with WMS/WFS services, graph theory (NetworkX), GDAL, and Snowflake.
Nice to have: CI/CD and orchestration tools (Airflow, Argo CD), Mapbox/MapLibre, Scala, Streamlit, DuckDB, and Power BI.

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
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