Chief Data Specialist / Chief Data Architect
As the Chief Data Specialist, you will lead a team and collaborate with business sponsors to deliver big data application projects. You have to grasp the latest big data technology trends, work with technical team to continuously enhance the big data platform to support ongoing digital transformation. You will also be in the steering role for data management activities including data governance, data standard, and data quality. Key Responsibilities
- Demonstrate expertise across multiple data disciplines and uplift the enterprise data application and management capabilities.
- Work closely with business sponsors to identify opportunities, analyze, and interpret trends or patterns.
- Take ownership of analytical projects end to end from extracting and exploring data, generating hypothesis, building structured analysis, and evaluating results.
- Track the latest developments and market dynamics of big data industry, constantly innovate and enhance design and solutions.
- Apply industry best practice to create scalable data platform that supports big data development, deployment, operation, and management.
- Establish and execute the mechanism of data governance (metadata management, data standard formation, data quality assurance etc.).
- Develop data standard and specifications, and monitor the implementation of data standard and specifications during the implementation of relevant projects.
- Develop data quality standards and data quality control plans, conduct data quality management, tracking and monitoring, and establish data quality evaluation systems.
- Extensive experience in one or multiple skills in data analytics or data science in the financial or digital domains.
- Strong team player, able to work members of different skills and experiences. Comfortable to operate in a complex matrix structure with multiple stakeholders.
- Proven experience in one or more of, customer segmentation, digital marketing, data science, portfolio analytics, use of open-source data in analyses.
- Proven experience in process and analysis of large amount of data using Python/ R
- Relevant degree in a one of these preferred disciplines, mathematics, computer science, data engineering, data science, analytics, statistics, econometrics, management information system, operations research.