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Data Analytics, Manager / Senior Manager - FS

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Hybrid

Data Analytics, Manager / Senior Manager - FS

Omni Group Asia Limited

Data Analytics, Manager / Senior Manager - FS

Skills

SQL QueriesPythonData ScienceData AnalysisPower BI

1 month ago

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Important information


Contract type:

Permanent

Salary:

HK$600,000 – HK$840,000 / year

Location:

Hong Kong

Work mode:

Hybrid

Published on:

18 September 2026

What they need


My client is a financial institution looking for an experienced Data Analytics, Manager / Senior Manager to join their team. They will be responsible for leading and advising the data team, generating business insights, and creating dashboards to ensure smooth operations. 

Responsibilities

  • Lead the cleansing of data, analyze complex datasets, and perform statistical analysis to uncover business opportunities, generate customer insights, and identify root causes for informed decision-making.
  • Architect and optimize data models and develop data pipelines to support analytical initiatives and data integrity across systems.
  • Collaborate with cross functional teams and work with senior stakeholders to create dashboards and prepare detailed reports and presentations.
  • Oversee data warehousing services, ensuring efficient data storage, retrieval, and governance
  • Coordinate with external vendors and service providers the integration of BI tools with data warehouse to business requirements
  • Undertake ad hoc tasks as assigned by leadership.

Key Requirements:

  • At least 6 years of relevant experience in data analytics preferably within the insurance or financial industry.
  • Bachelor’s or Master’s degree in Statistics, Data Science, Mathematics, Computer Science, or related fields.
  • Proficiency in Python, SQL, and PowerBI for data manipulation, analysis, and visualization.
  • Self-motivated with excellent problem-solving skills, a strong analytical mindset, and a proven track record in delivering impactful analytics solutions, innovation, and transformation.
  • Experience with data modeling, data pipelines, ETL processes, and working with large-scale structured and unstructured datasets.

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