Data Scientist – Financial Modelling Platform (Insurance Sector)
TeknektarWe are representing one of the world’s leading insurance software providers<\/b>, trusted by global insurers, reinsurers, and brokers to power decision -making and risk management. With innovation at the core of their mission, they provide advanced financial modelling platforms<\/b> that transform how insurance businesses operate, forecast, and manage risk.
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As part of continued growth, they are seeking a talented Data Scientist<\/b> to join their London -based team and help build next -generation predictive and financial modelling capabilities.
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As a Data Scientist<\/b>, you will be working on complex datasets and advanced statistical models that underpin the company’s cutting -edge financial modelling platform. You’ll collaborate with actuaries, software engineers, and product teams to deliver insights and solutions that directly shape how the insurance sector evaluates risk, pricing, and capital requirements.
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This is an exciting opportunity to work in a hybrid role that combines deep data science expertise with real -world financial impact<\/b> in a business that is shaping the future of insurance technology. Develop and deploy machine learning and statistical models<\/b> for insurance and risk -related financial modelling. Partner with actuaries, engineers, and product managers to translate business challenges into data -driven solutions. Analyse large -scale structured and unstructured insurance datasets to uncover insights and predictive patterns. Enhance the accuracy, scalability, and interpretability of the company’s financial modelling tools. Contribute to data pipelines, feature engineering, and model validation processes. Stay at the forefront of new techniques in ML/AI, actuarial modelling, and financial risk analytics. Essential:<\/b> 3+ years’ experience as a Data Scientist<\/b> (preferably in insurance, financial services, or risk analytics). Strong programming skills in Python<\/b> (Pandas, NumPy, Scikit -learn, TensorFlow or PyTorch). Solid knowledge of statistical modelling, probability, and machine learning techniques<\/b>. Hands -on experience with SQL<\/b> and data engineering for large datasets. Ability to explain complex models and findings to both technical and non -technical stakeholders. Desirable:<\/b> Background in insurance, actuarial science, or financial modelling<\/b>. Familiarity with capital modelling, Solvency II, or IFRS 17 frameworks<\/b>. Experience working with cloud platforms (AWS, Azure, or GCP). Exposure to big data technologies (Spark, Hadoop, Kafka) Qualifications:<\/b> BSc/MSc/PhD in Data Science, Computer Science, Mathematics, Statistics, or a related field. Professional certifications in AI/ML or actuarial sciences (desirable but not essential). Hybrid working model (flexible balance of office and home). Work with a world -leading insurance software business<\/b> impacting global financial markets. Career growth opportunities in a company that invests in learning and innovation. A collaborative culture where your expertise directly shapes the next generation of insurance technology.
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<\/div><\/span>Benefits<\/h3>
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