Role Description
We are scaling advanced analytics and AI across our portfolio of Pet Insurance brands, across claims, underwriting and customer operations. The purpose of this role is to provide expert technical leadership to the data science team responsible for delivering and maintaining data products powered by machine learning and AI. The Data Science Lead works with the business and functional leaders in shaping the portfolio of use cases, ensuring that value is realised and measured, and that relevant process, compliance and ethical requirements are met.
Key Responsibilities
* Lead the development of data science and AI solutions from inception to activation, providing hands‑on input and technical oversight of production‑grade machine learning and AI solutions.
* Coach onshore and offshore teams to deliver high-quality, compliant, and explainable models that improve customer outcomes and business KPIs.
* Manage, coach, and nurture talent within the data science / engineering pool, including performance, pay & rewards.
* Daily management of offshore teams (stand‑ups, backlog, sprint planning, QA) to ensure timely, quality delivery.
* Provide technical coaching & code review for Data Scientists/ML Engineers; establish standards for experimentation, MLOps, documentation, and testing.
* Prioritise the roadmap with Product Owners and business stakeholders; translate business problems into tractable ML and AI use cases.
* Drive best practices in model governance, risk management, and Consumer Duty alignment.
* Investigate new data and analytics technologies and contribute to the continual development and evaluation of the data architecture.
* Build and review end‑to‑end ML pipelines: data validation, feature engineering, model training, evaluation, and CI/CD to production.
* Develop models for insurance use cases such as automated claims processing, compliance, NLP on customer feedback, propensity & churn modelling, and underwriting pricing.
* Integrate pricing models into front‑end solutions and applications for quote‑to‑buy engines.
* Implement model monitoring (data drift, performance, fairness), alerting, and retraining schedules.
* Produce model documentation for governance committees.
* Partner with Claims, Underwriting, Pricing, Marketing, eCommerce, Compliance, Legal, and Customer Ops to embed models into decisions and workflows.
* Communicate complex findings and trade‑offs clearly to senior non‑technical stakeholders.
* Measure and track impact of the products developed through business KPIs at portfolio level.
* Run A/B and champion–challenger tests; quantify uplift and financial impact.
* Contribute to wider Group data science / AI initiatives and forums.
Location
This role offers flexibility to work in one of our UK‑based offices such as Bristol, Bournemouth, Ditton Park, Guildford, London or Birmingham. The role is hybrid, with an expectation of attending the office at least once per week.
Compensation
Pay: Circa £85,000 per year, based on experience, skills, and location. Salary is part of the total reward package.
Essential Skills
* MSc/PhD in a quantitative field (Statistics, Computer Science, Applied Math, Operational Research) or equivalent experience.
* Certifications in cloud, ML engineering, Responsible AI are welcome; practical delivery track record matters most.
* Proven leadership of offshore/nearshore technical teams.
* Guiding, inspiring, storytelling – communicating data insights to non‑technical audiences.
* Extensive experience using data science / machine learning and AI in insurance (P&C or other B2C sectors).
* Experience delivering tangible business benefit through end‑to‑end delivery, including deploying models to production.
* Operationalising machine‑learning models, integrating into business processes.
* Expert knowledge of Python, SQL, and at least one of LightGBM or XGBoost.
* MLOps experience: Git, CI/CD, containers, feature stores, model registry, experiment tracking, e.g., MLflow, SageMaker, Databricks, Azure ML.
* Hands‑on with NLP (transformers/LLMs, embeddings, prompt engineering, RAG) and classical machine learning.
* Solid grounding in model risk management, fairness, and explainability, ideally within regulated environments.
* Comfortable owning code reviews, architecture decisions, and performance optimisation for production workloads.
* Excellent communication and stakeholder engagement; able to frame ROI and align to Consumer Duty/customer outcomes.
Desirable Skills
* Experience with document AI/OCR (Azure Form Recognizer, AWS Textract) and claims automation.
* Time‑series and survival modelling for lapse/churn and claims frequency/severity.
* Experience with pricing and underwriting workflows, rules engines, and decisioning platforms.
* Familiarity with data privacy (GDPR), model governance, and internal model approval boards.
* Exposure to marketing analytics stacks (attribution, uplift modelling, next‑best‑action).
Benefits and Flexibility
* Flexible buy/sell holiday options.
* Hybrid working.
* Annual performance‑related bonus.
* Contributory pension scheme.
* Development days.
* Discounts up to 50% on a range of insurance products.
* Retail discounts.
* Volunteering days.
Our Commitments to Equality and Inclusion
We are a proud equal‑opportunity employer, committed to inclusion, gender equity, and balanced gender representation. We hold accreditations such as EDGE certified for gender inclusion, Women in Finance Charter member, Disability Confident employer, Stonewall Diversity Champion, Business in the Community’s Race at Work Charter signatory, and Armed Forces Covenant gold standard employer. We embrace neurodiversity and welcome applications from neurodivergent and disabled candidates, offering tailored adjustments to ensure success.
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