Responsibilities
* Champion analytics across the business: Advocate for the value and impact of analytics, showcasing the team's capabilities to influence business outcomes.
* Identify opportunities for value creation: Proactively seek new ways analytics can inform strategy, improve decision-making, and deliver measurable impact.
* Partner with stakeholders: Collaborate with internal and external teams to understand their analytical needs and inspire with the art of the possible.
* Solve complex business problems: Apply creative approaches to tackle challenges and unlock insights.
* Manage and coach analysts: Lead by example, fostering a culture of curiosity, collaboration, and continuous improvement.
* Own and optimise marketing selection models: Ensure models and processes are continuously refined for maximum effectiveness.
* Champion data quality and governance: Uphold high standards of data integrity, compliance, and governance across all analytical initiatives.
* Design and enhance reporting tools: Lead the development and optimisation of reporting tools which keep an eye on key KPIs.
Qualifications
* Proven experience in analytics, data science, or a related field, ideally within insurance or financial services.
* Demonstrable leadership experience, with a track record of developing analysts.
* Strong academic background in a numerical discipline (eg BSc Mathematics, Computer Science, Data Science).
* Proficiency in statistical and machine learning techniques (eg logistic regression, clustering, GBMs) and the application of these in a commercial context.
* Advanced SQL skills with experience with Python and/or R.
* Solid understanding of customer segmentation and its applications.
* Excellent communication and storytelling skills, with the ability to influence senior stakeholders.
* Strong organisational and strategic thinking capabilities.
* Resilience, can work independently to deliver projects
* Proactively share insights, results and identify risks, without prompting
* Proficient at communicating results in a concise manner both verbally and written
Desirable
* Postgraduate qualification in relevant field (eg Computer Science, Data Science, Operational Research)
* Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric).
* Familiarity with MLOps practices and version control tools (e.g. Git).
* Experience deploying and maintaining of ML models in production environments.
* Exposure to A/B testing and campaign optimisation techniques.
* Knowledge of marketing mix modelling and marketing performance metrics.
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