# Manager, Advanced Analytics at Prudential plc

Prudential plc is hiring a Manager, Advanced Analytics in Hong Kong, Hong Kong SAR China. Level rates it Builds AI ●●●●; you can [apply on Prudential plc](https://jobsbylevel.com/go/e5e0c1b6-48b0-4880-9bd1-82f16cd95916?utm_medium=ai-agent).

AI Level 4, AI centrality 94 out of 100. Hong Kong.

## Details

- Company: [Prudential plc](https://jobsbylevel.com/companies/prudential-plc)
- AI level: AI Level 4 (score 94 out of 100)
- Location: Hong Kong
- Posted: October 2, 2026
- Apply: https://jobsbylevel.com/go/e5e0c1b6-48b0-4880-9bd1-82f16cd95916?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=manager-advanced-analytics-at-prudential-plc-1c1aea

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## Description

Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed. The Data Analytics team is seeking a highly technical and hands-on Manager, Advanced Analytics to drive the development and deployment of machine learning and AI solutions across the business. This role will be responsible for designing, building, and operationalizing advanced analytical models that support customer growth, retention, distribution effectiveness, marketing optimization, and business transformation initiatives. Working closely with the Associate Director, Customer Insights & Advanced Analytics, the successful candidate will lead the technical delivery of predictive models, AI applications, and modern data science capabilities while helping establish best practices in machine learning engineering and MLOps. This role is ideal for a highly technical data scientist who enjoys solving complex business problems through advanced analytics, machine learning, and artificial intelligence. Job Responsibilities Advanced Analytics & Data Science Design, develop, validate, and deploy predictive and machine learning models to support customer acquisition, retention, repurchase, cross-sell, distribution productivity, and marketing effectiveness. Develop advanced analytical solutions including propensity models, churn prediction, customer lifetime value models, recommendation engines, forecasting models, and optimization algorithms. Apply modern machine learning techniques to identify business opportunities and improve decision making across customer, agency, marketing, and operational domains. Translate business challenges into scalable analytical and AI-driven solutions. AI & Machine Learning Innovation Explore and implement emerging AI technologies, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents where appropriate. Evaluate and prototype new AI use cases that enhance customer experience, operational efficiency, and business productivity. Drive innovation by identifying opportunities to leverage AI and advanced analytics across the organization. Model Engineering & MLOps Establish and manage end-to-end machine learning lifecycle processes, including model development, testing, deployment, monitoring, and retraining. Optimize model performance through feature engineering, hyperparameter tuning, model selection, and experimentation. Develop scalable and production-ready machine learning solutions in collaboration with technology and data engineering teams. Implement MLOps best practices to ensure model reliability, governance, scalability, and operational efficiency. Job Requirements Education Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Actuarial Science, or a related quantitative discipline. Master's degree or above is preferred. Experience Minimum 8-10 years of experience in data science, machine learning, advanced analytics, or related quantitative fields. Proven experience in developing and deploying machine learning solutions that deliver measurable business impact. Experience within insurance, financial services, telecommunications, e-commerce, or other data-intensive industries is preferred. Technical Expertise Strong expertise in machine learning, predictive modeling, statistical analysis, and optimization techniques. Hands-on experience with Python and machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or equivalent. Experience in feature engineering, model evaluation, hyperparameter optimization, and model

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