Data Manager / Data Team Lead

Hong Kong, HK

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We are looking for a Data Team Manager skilled in generative AI and analytics. Operating with minimal supervision, this role involves understanding the data needs across the organization and creating a roadmap to enhance data capabilities for automation and business insights. The manager will expand the data function as new automation use cases are implemented, converting data into insights that drive strategy and decision-making to support profitable growth. This role requires strong business acumen and expertise in generative AI techniques, AI tools and data analytics. Knowledge in data engineering is also beneficial.

 

Job Responsibilities:

  • Lead and manage a data engineering team of 3 people and a combined automation, generative AI, and customer analytics team of 2 people.
  • Develop and execute strategic projects focused on automation and generative AI to enhance business operations.
  • Understand and translate complex business requirements into effective data solutions.
  • Transform data and information into insights that inform high-level strategy and tactical decision-making in support of revenue and profitability objectives.
  • Implement and optimize data pipelines and workflows for improved efficiency and scalability.
  • Collaborate with cross-functional teams to align data initiatives with business goals.
  • Oversee the deployment of advanced generative AI techniques, including agentic RAG, to solve business challenges.
  • Provide mentorship and technical guidance to team members, fostering a culture of continuous learning and improvement.
  • Manage project timelines, budgets, and resource allocation effectively.
  • Communicate complex data concepts to non-technical stakeholders in a clear and compelling manner.
  • Identify opportunities for process improvement and automation within data operations.

 

Job Requirements:

  • Master degree in Computer Science, Data Science, Statistics, or a related field. or degree in actuarial science with a data proven records
  • Proven experience (10+ years) in data strategy, data management, or a related field, in the insurance industry.
  • Strong leadership and team management skills, with the ability to inspire and guide a team of data engineers and data scientists.
  • Strong understanding of the insurance industry, including underwriting, claims management, actuarial science, risk assessment, and pricing.
  • A strategic thinker and results oriented with a proven ability to analyse situations, diagnose problems, identify the key issues, establish and weigh up alternative courses of action and produce a logical, practical and acceptable solution.
  • Familiarity with advanced data analytics techniques, statistical modelling, machine learning algorithms, and data visualization tools (Power BI), and experience with retrieval-augmented generation (RAG) techniques. Proficiency in programming languages such as Python and familiarity with big data technologies (e.g., Hadoop, Spark) is required.
  • Excellent verbal and written communication skills. Ability to convey complex technical concepts to non-technical stakeholders and collaborate effectively across teams.
  • Strong problem-solving skills.

 

Why Zurich

 

At Zurich, we like to think outside the box and challenge the status quo. We take an optimistic approach by focusing on the positives and constantly asking What can go right? 

We are an equal opportunity employer who knows that each employee is unique - that’s what makes our team so great! 
Join us as we constantly explore new ways to protect our customers and the planet.
 

  • Location(s):  HK - Hong Kong 
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Leadership Jobs

Tags: Big Data Computer Science Data Analytics Data management DataOps Data pipelines Data strategy Data visualization Engineering Generative AI Hadoop Machine Learning Pipelines Power BI Python RAG Spark Statistics

Perks/benefits: Career development

Region: Asia/Pacific
Country: Hong Kong

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