Open for Both HCM And Ha Noi And Expat
Job Purpose
Lead and oversee the design, development, and application of advanced analytics solutions to generate actionable insights across customer journeys and product enhancements. The role focuses on consolidating and analyzing large-scale, unstructured Big Data to deliver high-impact, data-driven outcomes.
Continuously apply advanced programming methods, analytical processes, and emerging technologies to accelerate innovation, enhance decision-making, and strengthen the organization's analytics capabilities while staying aligned with industry trends and best practices.
Key Accountabilities
1. Data Solutioning
- Evaluate the effectiveness of analytical, statistical, and predictive models; monitor business performance against model outputs.
- Design, develop, and deploy advanced machine learning and deep learning solutions, including recommendation engines, customized predictive models, customer journey analytics, and graph-based models.
- Drive adoption and scaling of machine learning and big data techniques across multiple customer journeys and Agile squads.
- Manage and deliver complex data science initiatives in an Agile environment, ensuring compliance with internal governance and regulatory requirements.
2. Data Insighting
- Lead the identification, interpretation, and communication of meaningful, actionable insights from large-scale structured and unstructured data.
- Review and enhance processes and tools for monitoring model performance, data quality, and analytical accuracy.
- Proactively lead data-driven discussions across 3+ squads to define analytical questions, validate hypotheses, and address business challenges.
- Collaborate closely with Data Engineers to design and implement scalable, efficient analytical algorithms on enterprise analytics platforms.
3. Project Management
- Manage project risks, dependencies, conflicts, and evolving business requirements to ensure high-quality, on-time delivery.
- Partner with team leads and stakeholders to resolve people-related issues and unblock project challenges.
- Conduct post-mortems and root cause analyses to continuously improve delivery practices and team productivity.
4. Talent Development
- Mentor and coach Data Analysts in their development toward fully competent Data Scientists.
- Identify skill gaps and growth opportunities within the tribe and actively support capability development initiatives.
Key Relationships
Direct Reports:
- Data Analysts
- Data Scientists
Success Profile
Qualifications
- Bachelor's or Master's degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology, or a related field.
- Experience & Skills
- 7+ years of experience in data analysis, machine learning, and deep learning model development on large-scale datasets.
- Strong hands-on experience deploying statistical and machine learning models into production environments.
- Proficient in Python, R, Scala, SQL, Java, C/C++, Tableau, and database querying.
- Extensive experience in data mining, statistical analysis, data visualization, and advanced analytics solution development.
- Hands-on experience applying AI/ML in financial services or financial market use cases.
- Proven ability to deliver fact-based insights that support senior management decision-making and enterprise-wide value creation.
- Strong mastery of Agile Software Development, including Agile principles, Scrum methodologies, and cross-functional collaboration.
- Proven experience working in Agile teams and leading digital transformation initiatives end-to-end.
- English proficiency in accordance with bank's policy.
