Full Stack Data Scientist

A day in the life

This role is remote first but travel will occasionally be required to the London office (one day a month).

A day in the life

In this role, you will be at the forefront of our data-driven initiatives, training machine learning and artificial intelligence models as well as leveraging advanced statistical techniques to uncover trends and patterns that inform our business strategy. Your insights will play a key role in shaping decisions across various business areas, including marketing, sales, claims, customer retention, fraud detection, and customer servicing.

As a Full Stack Data Scientist, you'll collaborate closely with cross-functional teams, including product management and engineering, to identify an integrate your findings into our operations and develop predictive models that enhance our business processes. This collaborative approach allows you to work on a variety of projects, ensuring that your contributions have a significant impact across the organisation.

We value innovation and continuous improvement, so you'll be encouraged to stay current with emerging trends in data science and the pet insurance industry. You'll have the opportunity to evaluate and implement new methodologies, tools, and frameworks to keep our data analysis and modelling processes at the cutting edge.

Your responsibilities

• Manage data science and machine learning projects across the business.
• Develop predictive models that support key areas such as marketing, sales, claims, customer retention, fraud detection, and customer servicing.
• Deploy machine learning models into production using AWS services (SageMaker, S3, Feature Store), ensuring solutions are monitored, scalable, and production-ready
• Contribute to shaping and evolving our MLOps strategy, including model monitoring, retraining pipelines, and best practices for versioning and deployment.
• Evaluate and implement new tools and frameworks to improve our end-to-end ML lifecycle, from experimentation to production.
• Collaborate with product managers, engineers, and data engineers to integrate models and ensure robust data pipelines and infrastructure.
• Apply advanced statistical analysis, machine learning, and data mining to identify patterns and generate actionable insights.
• Communicate complex models and findings to stakeholders through visualisations, reports, and presentations.
• Stay updated on emerging trends in data science, ML/AI, and the pet insurance industry; implement new tools and frameworks to enhance workflows.
• Participate in Agile or Kanban methodologies, contributing to a collaborative, flexible team environment.
• Maintain strong awareness of data privacy and security requirements, ensuring compliance with relevant regulations.

Your skills and experience

• Hands-on experience in data science and machine learning, with strong proficiency in Python and SQL.
• Solid background in statistical analysis, ML techniques, and data mining.
• Familiarity with a range of ML models including Gradient Boosting Machines (GBMs), Neural Networks, and Large Language Models (LLMs).
• Practical experience with libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Strong knowledge of AWS products and services, particularly SageMaker, S3, and Feature Store, for model training and deployment.
• Experience with MLOps tools and practices, including model monitoring, CI/CD, and automation of ML workfl
• Comfortable working with cloud infrastructure and Infrastructure as Code (IaC), ideally with Terraform, to support scalable ML systems.
• Comfortable working with data engineering teams to ensure reliable pipelines and infrastructure.
• Ability to communicate effectively with both technical and non-technical audiences.
• Enthusiasm for working in an Agile/Kanban setup within a fast-paced, scale-up environment.