Senior Data Scientist (Optimization & Applied ML - Supply Chain Decision Systems)

Project overview

Senior Data Scientist contractor needed to build and improve large-scale decision systems for supply chain operations (routing, scheduling, resource allocation). The role is hands-on under a Data Science Lead, owning optimization and ML model components end-to-end: translating business constraints into MILP/heuristic formulations, integrating predictive ML inputs into optimization, debugging infeasibility/performance issues, and delivering scalable workflows in Python/SQL within Azure/Databricks. Strong stakeholder communication is required to explain assumptions, trade-offs, and outcomes.

Responsibilities

• Develop and enhance optimization models using MILP and heuristic approaches, applying them to problems such as vehicle routing, scheduling, and resource allocation, and improving performance using solvers such as Gurobi
• Apply machine learning techniques to support decision systems, including predictive modeling, feature engineering, and generating inputs for optimization models, while ensuring strong integration between ML and optimization frameworks
• Translate business requirements into structured analytical and optimization problems, incorporating operational constraints and clearly communicating model assumptions, trade-offs, and outcomes to stakeholders
• Diagnose and resolve model issues including infeasibility, performance bottlenecks, and data inconsistencies, while analyzing trade-offs across cost, service level, and operational feasibility
• Develop and maintain data workflows using Python and SQL, and support scalable processing and deployment within cloud environments such as Azure and Databricks
• Ensure data quality and model reliability by validating inputs, identifying gaps, and supporting feedback loops to improve model accuracy and alignment with operations
• Collaborate with cross-functional teams, take ownership of model components, contribute to technical design discussions, and provide guidance to junior team members

Requirements

• 8+ years experience in data science, operations research, or related field
• Optimization modeling (MILP)
• Vehicle Routing Problem (VRP) and/or routing optimization
• Scheduling optimization
• Resource allocation optimization
• Heuristic approaches for optimization
• Optimization solver experience (Gurobi)
• Applied machine learning (predictive modeling)
• Feature engineering
• Integration of ML outputs into optimization/decision systems
• Python
• SQL
• Model debugging (infeasibility diagnosis, performance bottlenecks)
• Data validation and data quality checks
• Ability to translate business requirements into analytical/optimization problems
• Communication with technical and non-technical stakeholders

Project details

• Start: flexible
• Remote: remote
• Location: Europe, United Kingdom, GB