Lead Data Scientist is an exciting remote opportunity at Brego, based Remote. This role is ideal for AI professionals looking to work from home while contributing to cutting-edge artificial intelligence projects. Read the full job description below and apply today.
Brego is an automotive technology company using AI and data analytics to help dealerships, lenders, and other industry partners make better vehicle valuation, pricing, and risk decisions. Working at the intersection of software, data, and decision-making, the team focuses on turning complex information into practical products that support smarter outcomes across the automotive market.
As a Lead Data Scientist, you will take ownership of the AI (custom neural networks rather than third-party LLM technology) and machine learning capabilities behind products that influence high-value pricing and risk decisions. This is a hands-on technical leadership role where you will be responsible for designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable business impact.
Responsibilities
Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation
Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics
Take responsibility for production model performance, reliability and long-term maintenance
Evaluate model performance and improve predictive accuracy across production models
Develop and maintain automated retraining pipelines to keep models effective over time
Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable
Design and run experiments, track results and use data to drive model improvements
Work closely with engineering and product teams to integrate models into production systems and deliver business value
Requirements
Must have:
5+ years of experience building and deploying machine learning models in production environments
Strong experience developing and training neural networks for real-world applications
Strong experience with the Python data science ecosystem, including pandas, NumPy and scikit-learn
Hands-on experience with PyTorch or TensorFlow
Strong understanding of machine learning, statistics, and model evaluation methodologies
Experience taking machine learning models from concept through deployment and ongoing production ownership
Experience evaluating model performance, improving predictive accuracy, and maintaining retraining pipelines, model monitoring, and experiment tracking
Experience with feature engineering and working with large, real-world datasets
Experience writing clean, maintainable, production-quality Python code
Experience with SQL for data analysis and data manipulation
Experience deploying ML workloads in cloud environments
Ability to independently own technical projects and make sound engineering decisions with minimal supervision
Strong problem-solving skills with the ability to investigate complex data and modelling challenges
Strong communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders
Experience collaborating with software engineers, product managers, and data engineers
Eligible to work in the UK
Nice to have:
Experience in the automotive industry or with vehicle data
Experience in pricing, forecasting, risk modelling, or other predictive analytics domains
Experience with MLOps tooling and infrastructure
Experience building automated data and model pipelines
Experience mentoring or providing technical leadership to other data scientists or engineers
Benefits
Competitive salary of £90,000 - £110,000 per year, depending on experience
Private healthcare
Pension scheme
Fully remote role with flexible working hours
Working from home allowance
Choice of Apple MacBook Pro or high-spec Windows workstation
Learning and progression opportunities
Optional access to our Silverstone office. The team usually meets there around one day per week, but attendance is entirely optional
High levels of ownership and autonomy with the opportunity to shape the company's AI strategy
Collaborative, low-bureaucracy engineering culture that values autonomy, integrity and innovation
Regular company social events
25 days annual leave plus 3 additional days between Christmas and New Year
