JOB DESCRIPTION
1. Building data platform: - Survey business requirements, exchange with Biz owner/ Product Owner, relevant business departments to understand data generation processes from systems in order to build data source description documents and data organization design documents. - Build formula sets to ensure data quality and verify data accuracy. - Build dictionary documents on classification and definition of data types to record data fields from sources, ensuring scientific, logical and consistent data. - Design data processing layers from raw data, aggregated data, master data to ensure optimization for data access control and exploitation tasks. - Build data models and business models, backtest data for business mechanisms serving analysis objectives according to leadership requirements.
2. Building reports/analyzing insights, visualizing data for users: - Understand business or operational problems and build integration flows, design data calculation tasks providing reports, aggregated data for the company's digital platforms. - Use data visualization tools to build management reporting systems, automated reports, design charts and graphs suitable for requirements from Biz owner/leadership.
3. Ensuring quality, standards and standardization of data infrastructure: - Support with Data governance/Data engineer departments and other product teams to build data definition sets and standardize input data ensuring consistency, accuracy and timeliness of data. - Build data-driven culture across departments and divisions of the organization. - Build and comply with organization's metadata and data catalog standards.
4. Project management: - Build master plan for tasks, track project progress, manage risks and report to stakeholders. - Use project management tools such as Microsoft Project, Trello... to closely follow development requirements during project implementation to communicate timely and ensure the project is on track. - Be responsible for explaining results and progress of assigned projects.
5. Training and team development: - Build training courses on the training system on using visualization tools and data design documents, data modeling - Support new staff in grasping working methods. - Coordinate resources for implementation and evaluate work results of staff in projects. - Provide end-user support in using software systems according to training support documents or other development teams on data integration according to API documents or datasets provided by the department.
6. Process improvement and automation of data processing and reporting flows: - Evaluate current processes, identify unsuitable points and areas needing improvement. - Record pain points and requirements from stakeholders to proactively propose coordination processes between source systems, operations departments, application operations departments to improve processes, enhance data quality and reduce manual data entry requirements. - Periodically review and support building data improvement processes.
7. Research and professional development capability: - Understand industry operational problems, refer to market best practices to meet customer-centric objectives in specialized domains such as transaction operations, banking finance, F&B. - Understand new tools and techniques, exchange with data engineer/Data architect teams to propose solutions to problems, meet timely requirements for data development and use of the organization.
CANDIDATE REQUIREMENTS
1. Education/Certificates
- Bachelor's degree in business administration, information technology, banking finance, with international certificates such as CFA, CAAC is an advantage.
2. Work experience
- At least 3-5 years of experience in business analysis field, priority given to candidates with experience in finance, securities, insurance industries.
3. Knowledge/Professional competencies/Skills
- Excellent analytical skills, critical thinking and problem-solving.
- Good communication and presentation skills.
- Proficient use of data analysis tools and project management software.
- Skills in writing clear, logical analytical documents, ensuring sufficient development features.
- Skills in collecting, processing data and using data for analysis objectives (Applying DIKW model).
- Skills in using design and documentation modeling tools: UI-UX tool, visio, Figma...
- Skills in analyzing financial industry business problems.
- Skills in using data visualization tools.
- Knowledge about data governance.
- Project management and change management skills.
- Skills in using AI and big data/AI and big data proficiency.
- Systems thinking.
- Customer thinking and service orientation.
4. Core competencies
- Have qualities and mindset suitable with the company's core values.
BENEFITS AND ENTITLEMENTS
1. Community of ethical professionals dedicated to service
- Professional financial industry work environment.
- Work with spirit of ownership, creativity and challenge.
2. Total income according to competency
- Income commensurate with competency and contribution value.
- Consider annual income adjustments.
3. Treatment regime
- Participate in social insurance, health insurance, unemployment insurance according to labor law regulations.
- Participate in health insurance and 24/24 accident insurance.
4. Learning organization and vibrant culture
- Open workspace with modern equipment.
- Rich and meaningful cultural activities, team building, charity activities.
