Senior Data Scientist
Cox Automotive Europe ¦ Data Solutions ¦ Manchester
About Cox Automotive Europe
Cox Automotive Europe is one of the largest automotive services businesses in the UK and Europe, providing end-to-end solutions across vehicle remarketing, fleet management, financial services and dealer software. Our Data Solutions team sits at the heart of this — building the intelligence layer that powers decisions across our business and for our OEM and fleet clients.
The Role
This is a senior individual contributor role within our Data Solutions team, reporting to the Lead Data Scientist. You will be a key part of our ambition to build a world-class data intelligence capability.
Your primary focus is the Decision Engine — a recommendation product we are building for major OEM clients, starting with Stellantis. The Decision Engine helps remarketing managers assess, price, channel and act on hundreds of vehicles in a single working session. Getting the underlying models right — and proving they work — is the difference between a product that gets used and one that gets ignored.
Beyond the Decision Engine, you will contribute to a growing intelligence capability that serves multiple business units across Cox Automotive Europe. This is not a role where you disappear into a notebook for six months. You will work closely with product managers, domain experts and engineers, and you will be expected to make your work land.
What You Will Work On
Decision Engine models Building and owning the core models that underpin the Decision Engine — pricing intelligence, stock segmentation, buyer behaviour profiling, and channel optimisation. These models need to be accurate, explainable, and deployable into a production environment used daily by Stellantis remarketing managers across multiple European markets.
Counterfactual measurement Designing the framework that proves the Decision Engine works — what would have happened to vehicles that weren't acted on by DE recommendations? This is one of the most important and most technically interesting problems on the roadmap. Without it, we cannot credibly demonstrate commercial impact to clients or to ourselves.
Model explainability Building the trust layer. Remarketing managers will not act on recommendations they don't understand. You will design explainability outputs — reason codes, confidence indicators, contributing factors — that make model outputs interpretable by non-technical users in a high-pressure working environment.
Pricing intelligence Working alongside our Vehicle Data and Pricing capability to model OEM pricing decisions that account for residual values, market conditions, buyer segmentation and commercial policy. This is a complex, high-stakes domain — the kind of problem that rewards deep thinking over fast iteration.
Raising the team's ceiling You will be a senior voice in a team of five. You will share knowledge, review others' work, and help build a culture where the team learns faster collectively than any individual could alone.
What We Are Looking For
Essential
* Strong data science fundamentals — production-grade experience in machine learning, statistical modelling, time-series analysis or pricing/propensity modelling
* Proven track record of building models that go into production and stay there — not just analysis, but deployable, monitored, maintainable outputs that a product team can rely on
* Experience working in or very close to a commercial domain — you understand how businesses make decisions from data, not just how models work in isolation
* Comfortable working independently at pace — this role does not come with a lot of hand-holding; you need to be able to take a problem, break it down, and deliver
* Strong communication skills — you can explain model outputs and their limitations to product managers, engineers and senior stakeholders without hiding behind jargon
Essential (continued)
* Experience in automotive, vehicle remarketing, fleet management or fleet disposal — you understand how vehicles are valued, aged, channelled and priced, and you can apply that context to model design without needing to be briefed from scratch
* Familiarity with explainable AI techniques — SHAP, LIME, feature importance frameworks — and an instinct for when and how to apply them in a user-facing product
* MLOps experience — experiment tracking (MLflow, Weights & Biases), model monitoring, drift detection, automated retraining pipelines
* Experience with Databricks or a comparable lakehouse platform
* Python or R proficiency across the standard DS stack — pandas, scikit-learn, PyTorch or TensorFlow where relevant
* Experience with PySpark desirable
The Team and Culture
You will join a team of six data scientists and analysts, within a broader Data Solutions function of approximately 20 people. The team is at an inflection point — moving from a reactive, project-by-project way of working toward a product-led intelligence capability that multiple OEM clients and internal business units will consume.
We are investing in modern tooling — Databricks as our platform, AI-assisted development as standard practice, and an AIT squad model that embeds data science directly into product delivery. If you have been frustrated by data science teams that build models nobody uses, this is the environment where that changes.
We are a team that takes quality seriously and ships things. We value people who can hold both of those things at once.
What We Offer
* Competitive salary commensurate with senior experience
* Access to Cox Automotive's broad European business as a domain for genuinely interesting problems
* A team that is growing and a function that has senior executive support and commercial backing
Location
Manchester. Occasional travel to client sites and team locations required.
STRICTLY NO AGENCIES PLEASE
We work with a carefully selected set of recruitment agencies and we're not looking to add to our PSL.
We do not accept unsolicited agency CV's sent to the recruitment team or directly to the hiring manager. We will not be responsible for any fees related to unsolicited CV's.