[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-manager-advanced-analytics-prudential-hong-kong-limited-de-hk":3},{"id":4,"slug":5,"title":6,"description":7,"company":8,"is_featured":11,"featured_until":7,"is_active":12,"deactivated_at":7,"is_enriched":12,"processed_job_posting_json":13,"processed_latitude":76,"processed_longitude":78,"processed_employment_types":80,"processed_working_hours":81,"processed_working_hours_labels":83,"processed_home_office":84,"processed_salary_min":73,"processed_salary_max":74,"processed_salary_currency":70,"processed_salary_source":85,"processed_benefits":86,"processed_benefits_labels":89,"processed_industry":90,"processed_skills":7,"processed_job_location":91,"processed_full_address_gmaps":93,"processed_street_gmaps":95,"processed_city_gmaps":96,"processed_postal_code_gmaps":97,"processed_country_gmaps":98,"processed_country_iso_code_gmaps":99,"full_description":16,"formatted_description":101,"processed_employment_types_labels":24,"processed_home_office_labels":22,"processed_industry_labels":26,"processed_it_skills":102,"processed_it_skills_labels":105,"processed_soft_skills":106,"processed_soft_skills_labels":107,"processed_job_expertise_skills":108,"processed_job_expertise_skills_labels":109,"processed_language_requirements":110,"processed_total_experience_years":117,"processed_professional_field":118,"processed_professional_field_labels":121,"processed_leadership_role":12,"processed_date_posted":20,"raw_job_url":122,"apply_url":7,"raw_hiringOrganization_logo_url":7,"translations":7,"canonical_industry_key":123,"canonical_industry_label":124,"max_cpc":125,"actual_cpc":7},86455,"manager-advanced-analytics-prudential-hong-kong-limited","Manager, Advanced Analytics",null,{"name":9,"slug":10,"logo_url":7},"Prudential Hong Kong Limited","prudential-hong-kong-limited",false,true,{"@context":14,"@type":15,"title":6,"description":16,"hiringOrganization":17,"datePosted":20,"validThrough":21,"jobLocationType":22,"employmentType":23,"industry":25,"skills":27,"baseSalary":68},"https:\u002F\u002Fschema.org\u002F","JobPosting","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 explainability. Strong understanding of MLOps, including model deployment, monitoring, version control, CI\u002FCD, and production model management. Experience working with cloud-based analytics and AI platforms such as Azure, AWS, or GCP. Familiarity with Generative AI, LLMs, vector databases, RAG architectures, agentic workflows, and modern AI technologies is highly desirable. Strong SQL and data manipulation capabilities with experience handling large-scale structured and unstructured datasets. Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time \u002F fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements. We are Prudential. For every life, we are partners. For every future, we are protectors. Prudential plc provides life and health insurance and asset management to 17 million customers across 20 markets in Asia and Africa. We are headquartered in Hong Kong and have dual primary listings on the Stock Exchange of Hong Kong and the London Stock Exchange. We are focused on four strategic regions: Greater China, ASEAN, India and Africa. Our customers are served by around 55,000 agents and more than 200 bank partners. Prudential plc is not affiliated in any manner with Prudential Financial, Inc., a company whose principal place of business is in the United States of America or with the Prudential Assurance Company, a subsidiary of M&G plc, a company incorporated in the United Kingdom. Find out more at www.prudentialplc.com Follow us on LinkedIn",{"@type":18,"name":19},"Organization","PHKL Prudential Hong Kong Limited","2026-10-02","2027-10-02","ONSITE",[24],"PERMANENT",[26],"Insurance and Financial Services",[28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],"Python","Scikit-learn","XGBoost","LightGBM","TensorFlow","PyTorch","SQL","Azure","AWS","GCP","MLOps","CI\u002FCD","Version Control","Generative AI","Large Language Models (LLMs)","Retrieval-Augmented Generation (RAG)","Vector Databases","AI Agents","Communication","Collaboration","Problem-solving","Innovation","Leadership","Machine Learning","Predictive Modeling","Statistical Analysis","Optimization Techniques","Feature Engineering","Model Evaluation","Hyperparameter Optimization","Model Explainability","Data Manipulation","Model Deployment","Model Monitoring","Production Model Management","Customer Lifetime Value Modeling","Churn Prediction","Recommendation Engines","Forecasting Models","Propensity Models",{"@type":69,"currency":70,"value":71},"MonetaryAmount","HKD",{"@type":72,"minValue":73,"maxValue":74,"unitText":75},"QuantitativeValue",800000,1200000,"YEAR",[77],22.3193039,[79],114.1693611,"permanent",[82],"FULL_TIME",[82],"onsite","estimated",[87,88],"Equal opportunity employer","Reasonable adjustments for physical or mental health requirements",[87,88],"insurance and financial services",[92],"phkl, phkl | one island east 28\u002Ff, hong kong",[94],"Hongkong",[],[],[],[94],[100],"HK","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.\n\nThe 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.\n\n## Job Responsibilities\n\n### Advanced Analytics & Data Science\n\n- Design, develop, validate, and deploy predictive and machine learning models to support customer acquisition, retention, repurchase, cross-sell, distribution productivity, and marketing effectiveness.\n- Develop advanced analytical solutions including propensity models, churn prediction, customer lifetime value models, recommendation engines, forecasting models, and optimization algorithms.\n- Apply modern machine learning techniques to identify business opportunities and improve decision making across customer, agency, marketing, and operational domains.\n- Translate business challenges into scalable analytical and AI-driven solutions.\n\n### AI & Machine Learning Innovation\n\n- Explore and implement emerging AI technologies, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents where appropriate.\n- Evaluate and prototype new AI use cases that enhance customer experience, operational efficiency, and business productivity.\n- Drive innovation by identifying opportunities to leverage AI and advanced analytics across the organization.\n\n### Model Engineering & MLOps\n\n- Establish and manage end-to-end machine learning lifecycle processes, including model development, testing, deployment, monitoring, and retraining.\n- Optimize model performance through feature engineering, hyperparameter tuning, model selection, and experimentation.\n- Develop scalable and production-ready machine learning solutions in collaboration with technology and data engineering teams.\n- Implement MLOps best practices to ensure model reliability, governance, scalability, and operational efficiency.\n\n## Job Requirements\n\n### Education\n\n- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Actuarial Science, or a related quantitative discipline.\n- Master's degree or above is preferred.\n\n### Experience\n\n- Minimum 8-10 years of experience in data science, machine learning, advanced analytics, or related quantitative fields.\n- Proven experience in developing and deploying machine learning solutions that deliver measurable business impact.\n- Experience within insurance, financial services, telecommunications, e-commerce, or other data-intensive industries is preferred.\n\n### Technical Expertise\n\n- Strong expertise in machine learning, predictive modeling, statistical analysis, and optimization techniques.\n- Hands-on experience with Python and machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or equivalent.\n- Experience in feature engineering, model evaluation, hyperparameter optimization, and model explainability.\n- Strong understanding of MLOps, including model deployment, monitoring, version control, CI\u002FCD, and production model management.\n- Experience working with cloud-based analytics and AI platforms such as Azure, AWS, or GCP.\n- Familiarity with Generative AI, LLMs, vector databases, RAG architectures, agentic workflows, and modern AI technologies is highly desirable.\n- Strong SQL and data manipulation capabilities with experience handling large-scale structured and unstructured datasets.\n\nPrudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time \u002F fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.\n\nWe are Prudential. For every life, we are partners. For every future, we are protectors.\n\nPrudential plc provides life and health insurance and asset management to 17 million customers across 20 markets in Asia and Africa. We are headquartered in Hong Kong and have dual primary listings on the Stock Exchange of Hong Kong and the London Stock Exchange. We are focused on four strategic regions: Greater China, ASEAN, India and Africa. Our customers are served by around 55,000 agents and more than 200 bank partners. Prudential plc is not affiliated in any manner with Prudential Financial, Inc., a company whose principal place of business is in the United States of America or with the Prudential Assurance Company, a subsidiary of M&G plc, a company incorporated in the United Kingdom. Find out more at www.prudentialplc.com Follow us on LinkedIn",{"aws":103,"gcp":103,"sql":104,"azure":103,"ci\u002Fcd":103,"mlops":104,"python":104,"pytorch":104,"xgboost":104,"lightgbm":104,"ai agents":103,"tensorflow":104,"scikit-learn":104,"generative ai":103,"version control":103,"vector databases":103,"large language models (llms)":103,"retrieval-augmented generation (rag)":103},3,4,[28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],{"communication":104,"collaboration":104,"problem-solving":104,"innovation":104,"leadership":104},[46,47,48,49,50],{"churn prediction":104,"machine learning":104,"model deployment":104,"model evaluation":104,"model monitoring":104,"data manipulation":104,"propensity models":104,"forecasting models":104,"feature engineering":104,"predictive modeling":104,"model explainability":104,"statistical analysis":104,"recommendation engines":104,"optimization techniques":104,"hyperparameter optimization":104,"production model management":104,"customer lifetime value modeling":104},[51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],{"detected_language_jobad":111,"required":112},"en",[113],[114],{"language":115,"level":116},"ENGLISH","C1",8,[119,120],"Information and Communications Technology Professionals","Mathematicians, Actuaries and Statisticians",[119,120],"https:\u002F\u002Fprudential.wd3.myworkdayjobs.com\u002Fen-us\u002Fprudential\u002Fjob\u002Fhong-kong\u002Fmanager--advanced-analytics_26090313","insurance","Insurance",1]