Tom Murarik
Decision Scientist | Optimisation and Forecasting
About
I build end-to-end decision systems that optimise real-world logistics. At Ocado Logistics I have ownership of key projects, driving millions of pounds of savings in logistics costs. Leveraging mathematical skills, best practices in software development as well as business acumen, I devise and deliver high-impact end-to-end solutions for the Ocado Group's retail partners.
It is my belief that a modern day decision scientist should be able to break down a problem like an MLE, write code like a software engineer, deploy like a cloud expert and engage with stakeholders like a business analyst. I have extensive experience in solving problems in industry with this approach. In particular, I specialise in VRPs and time-series forecasting. I bring a pragmatic approach to my work: the stakeholder interpretability, deployment & maintainability of solutions takes priority over unnecessary mathematical complexity.
Experience
- Network Optimisation: solving highly constrained facility location problems using metaheuristic frameworks. With large-scale ensemble simulations, directly informed the decision of new Customer Fulfilment Center locations as part of Ocado's expansion strategy.
- Multi-Objective Optimisation: deciding optimal driver shifts by pairing this approach with Monte Carlo simulations leading to significant improvement in routing efficiency metrics and changes in driver hiring/headcount.
- VRPs: improving routing efficiency by enabling parallelisation and integrating cutting-edge new algorithms on the optimisation framework that routes the tens of thousands of vans used by the Ocado Group's retail partners.
- Time-series forecasting: deployed tree-based ML models across the business, applications include hourly sales and basket size forecasting. Automated manual methods and decreased forecast error by up to half vs manual Excel-based legacy methods.
- MLOps: created centralised ML forecasting pipeline templates, enabling easy repeated use across three separate retailers. Suitable for templating new forecasting projects across teams.
- Decision Model Deployment: deployed optimisation algorithms for use by analysts; included dynamic right-sizing of VM depending on problem size, easily accessible solution storage and Streamlit UI.
- Cloud: ownership of business-critical pipelines, including hourly refreshes of key forecasts and the cloud cost vs benefit trade-off of running these models. Extensively involved in set-up and architecture of GCP eco-system.
- SWE: development of heuristic architectures in Scala for a SoTA VRP solver trusted by multi-national haulage companies such as Kuehne + Nagel.
- Heuristics: improved optimiser performance while decreasing run-time, presented at the VeRoLog conference Jun 2025.
- DNNs: work on PyTorch models that predict loading times for trucks depending on the content of the load, providing better bounds for the overlying optimisation model.
- Stakeholder engagement: secured new business from cash-and-carry providers at industry conferences.
- Agile work in interdisciplinary teams; taking mathematical concepts from client spec to development to deployment.
- ML & Databases: built DNN pipelines for classifying card properties and tracking stock in SQLite.
- APIs: created RESTful APIs that allowed stock to be listed on e-commerce vendors seamlessly.
- Robotics: card-sorting arm prototype, attached a phone camera to an Arduino robot arm to allow automation of manually-intensive tasks of sorting new stock.
Education
Dissertation: "A Multi-Objective Evolutionary Search Strategy for Feature Selection in Machine Learning Models"
Developed a novel evolutionary algorithm approach for feature selection in ML customer churn classification for Vodafone Data Analytics. I self-sourced this dissertation in industry, it was not available as an option in the pre-prepared list of projects from the university. The work demonstrated significant improvements over traditional feature selection methods across multiple benchmark datasets, and is available as a pre-print.
🥈 Runner-up in the Operational Research Society's May Hicks Award
BSc Chemistry
Graduated 2020University College London
Grade: First-Class Honours
Awards
Engagement
Timeline
New Role: Senior Data Scientist
Ocado Logistics
Presented: VeRoLog Conference
Hosted at University of Trento, Italy
Awarded: May Hicks Award - Runner-Up
Operational Research Society
New Role: OR Software Developer
Optrak Vehicle Routing Software
Graduated: MSc with Distinction
University of Edinburgh
Started: MSc Operational Research
University of Edinburgh
New Role: Software Engineer
WeBuyAnyCard
Graduated: BSc Chemistry
University College London