Lead Data Scientist

🔥 3 hours ago

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Brego

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

🚘 Automotive

🤖 Artificial Intelligence

☁️ SaaS

💰 $206.9k Seed Round - Brego on 2021-10

Automotive • Artificial Intelligence • SaaS

Brego is an AI-driven automotive valuations and analytics company providing a SaaS platform and API for businesses across the vehicle market. Its flagship Brego Platform uses neural-network models and a large vehicle database (claimed 1. 2 billion data points) to deliver real-time current and future valuations, stock sourcing and analytics, vehicle checks, and downloadable reports. Brego markets specialized solutions for dealers, lenders, brokers and insurers (Brego-Dealer, Brego-Broker, Brego-Insurer), and emphasizes fast API valuation calls, compliance and risk tools, and broad coverage across cars, vans, bikes, motorhomes, caravans and more.

📋 Description

• 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

• 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.