Senior Data Scientist
Senior Data Scientist | Python ML | AUC-ROC | Dataiku | BigQuery | EducationTech | Remote, London | £80k Looking to help shape Data Strategy for a scaling Tech-for-Good business I'm partnered with a AI-first data and analytics platform built for schools, multi-academy trusts and education groups. Their technology connects fragmented school data - attendance, behaviour, wellbeing, assessment, SEND and unstructured documents - and uses a multi-agent AI system to surface actionable insights for school leaders in seconds.They are in a high-growth phase, backed by Innovate UK funding, with a roadmap spanning predictive analytics, supplier intelligence, and international expansion. The team is mission-driven, remote-first, and growing quickly - every hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education dataset.You’ll be the senior technical lead for ML research, shaping modelling strategy and ensuring outputs are robust, explainable and production-ready.Core Responsibilities:
- Predictive Model Development: Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data.
- Feature Engineering: Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets.
- Evaluation & Methodology: Establish rigorous evaluation frameworks including AUC-ROC, precision/recall, cross-validation and holdback validation.
- ML Platform Ownership: Use Dataiku for pipeline development, model training and deployment.
- Stakeholder Communication: Present findings clearly to non-technical audiences such as school leaders and grant reviewers.
- Bias & Fairness Analysis: Ensure models meet fairness, transparency and explainability standards.