Lead Data Scientist

About the company

Brego is an automotive technology business that applies AI and data analytics to improve how dealerships, lenders, and other partners make decisions about vehicle valuation, pricing, and risk. The organisation sits at the crossroads of software, data, and decision support, creating practical products from complex information to help the automotive market make better choices.

Role overview

This position is a senior, hands-on technical leadership role focused on the AI and machine learning systems that power products used for high-value pricing and risk decisions. The role uses custom neural networks rather than third-party large language model technology. You will be accountable for the full lifecycle of production machine learning systems, including feature engineering, model training, deployment, monitoring, retraining, and continuous improvement. While working independently, you will also partner closely with engineering and product teams to deliver clear business outcomes.

Responsibilities

• Take full ownership of machine learning models in production, from defining the problem to deploying and continuously improving the solution.
• Develop, train, and release artificial neural network and machine learning models for vehicle valuation, pricing, and related analytics use cases.
• Be accountable for production model reliability, performance, and long-term upkeep.
• Assess model quality and find ways to improve predictive accuracy across live systems.
• Create and maintain automated retraining workflows so models stay effective over time.
• Track deployed models, troubleshoot problems, and implement enhancements to preserve accuracy and stability.
• Plan and run experiments, capture outcomes, and use the findings to improve model performance.
• Work in close collaboration with engineering and product partners to embed models into production systems and drive business value.

Requirements

• At least 5 years of experience creating and shipping machine learning models into production environments.
• Strong practical background in building and training neural networks for real-world applications.
• Deep familiarity with the Python data science stack, including pandas, NumPy, and scikit-learn.
• Hands-on experience using PyTorch or TensorFlow.
• Solid grounding in machine learning, statistics, and model evaluation techniques.
• Proven experience taking ML solutions from initial concept through deployment and ongoing ownership.
• Experience improving model performance, maintaining retraining pipelines, monitoring live models, and managing experiment tracking.
• Experience with feature engineering and working with large-scale, real-world datasets.
• Ability to write clean, maintainable, production-ready Python code.
• Experience using SQL for analysis and data manipulation.
• Experience deploying machine learning workloads in cloud environments.
• Comfort taking independent ownership of technical projects and making sound engineering decisions with limited supervision.
• Strong analytical problem-solving skills, especially when working through complex data and modelling issues.
• Excellent communication skills, with the ability to explain technical ideas to both technical and non-technical audiences.
• Experience working alongside software engineers, product managers, and data engineers.
• Must be eligible to work in the UK.
• Bonus experience includes automotive data, vehicle data, pricing, forecasting, risk modelling, predictive analytics, MLOps tooling, automated data/model pipelines, and mentoring or technical leadership for other data scientists or engineers.

Benefits

• Competitive pay in the range of £90,000 to £110,000 per year, based on experience.
• Private healthcare coverage.
• Pension scheme.
• Fully remote working with flexible hours.
• Home working allowance.
• Choice of an Apple MacBook Pro or a high-spec Windows workstation.
• Learning and career progression opportunities.
• Optional access to the Silverstone office, with the team typically meeting there about once a week, though attendance is not required.
• High ownership and autonomy, with the opportunity to help shape the company’s AI direction.
• A collaborative, low-bureaucracy culture that values autonomy, integrity, and innovation.
• Regular social events with the company team.
• 25 days of annual leave, plus 3 extra days between Christmas and New Year.

Work arrangement

This is a fully remote role, though the Silverstone office is available optionally. The team generally meets there around one day per week, but attendance is not mandatory.

Additional information

The role is for a UK-based candidate who can work independently and take responsibility for end-to-end machine learning delivery in a product-focused environment.