Data Scientist

Welcome to Hastings Direct We’re a digital insurance provider with a clear strategy to become the best and biggest player in the UK market. As a company, we’ve made huge investments in our technology, pricing, data and analytics capabilities over the past few years, along with nurturing our 4Cs culture and substantial investment in our people. And as a Finance team, we're doing exactly the same – building a market leading finance technology platform, investing in our team and our approach to leadership development, with a real focus on commercially adding value to the business.  The fact you’re now reading this job advert means we’ve tempted you to find out more about #lifeatHD. If you like what you see, we hope you'll consider joining our team.   We have high standards and understand some people may not apply for jobs unless they feel they tick every box. If you’re excited about joining us and think you have some of what we are looking for, even if you’re not 100% sure, we would love to hear from you.   Job Title: Data Scientist Location: Bexhill/Leicester/London – Hybrid Unfortunately, we are unable to offer sponsorship for this position Role Purpose    The Data Scientist will assist in the design, development, and deployment of predictive models that feed into Hastings’ market-leading pricing activities. This role is within a team of Data Scientists championing machine learning (ML) techniques to improve predictive performance using vast amounts of customer information.      Accountabilities    Your responsibilities will include:   Develop and support predictive models to assess insurance risk and inform pricing and underwriting decisions. Contribute to the integration of models into production systems and support their ongoing monitoring and maintenance. Develop, maintain and improve reusable tools, pipelines and processes that enable efficient, reliable and reproducible modelling, following agreed standards for coding, documentation, testing and model development. Identify, assess and prepare new data features, evaluating their predictive value, stability, interpretability and potential impact on customer pricing outcomes.   Skills, Knowledge & Experience    Essential    Experience building and evaluating predictive models such as linear and gradient boosted models. Proficiency using Python and appropriate machine-learning libraries. Proficiency in SQL, including preparing and transforming data for predictive modelling. Basic knowledge of Git or other code version control systems. Strong communication skills and time management skills. Demonstrable experience delivering data science solutions that have influenced business decisions and generated measurable commercial value. Desirable    Experience using Azure Machine Learning Studio or similar cloud-based ML platforms.  Experience using Snowflake or similar cloud-based data platforms. Experience in general insurance.   Personal Attributes    Natural problem…