Analytics Engineer

About the role

Bupa is looking for an Analytics Engineer to deliver and put into production Data Science (including Machine Learning and Gen AI) and Analytics projects that improve health insurance customer outcomes, in line with the business strategy and customer analytics roadmap. The role works closely with the data program and data technology teams to migrate from legacy systems to the new Azure data platform, and implements an MLOps framework for a set of propensity models used in customer recommendations, offers and 1-1 marketing campaigns.

Key responsibilities

• Support the Customer Insights and Decision Science team with data assets and pipelines for feature development and insights.
• Work with business stakeholders to turn their requirements into data-driven approaches.
• Build data pipelines from acquisition and ingestion through the data lake to reports, dashboards, applications, models and APIs.
• Engineer data features, reusing them across models and areas of the business via the feature store.
• Set up data quality monitoring for key datasets and the inputs and outputs of advanced analytics.
• Follow Bupa's designs, standards, guidelines and patterns.

Required profile

• 3+ years of experience in customer analytics, data science, data engineering or a similar field.
• Focus on cloud-first engineering, data processing frameworks, modern data management, agile working, automation and efficiency.
• Qualified in a quantitative discipline such as statistics, engineering, physics, mathematics, econometrics, computer science, machine learning or a related field.

Required skills

• SQL/TSQL (mandatory)
• Python (preferred)
• Azure data services, Azure Synapse, Azure SQL DW, Azure DataBricks/Spark, Azure ML and Power BI (preferred)