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Hướng dẫn ứng tuyển
Bước 1: Điền vào Mẫu thông tin ứng viên LOTTE Finance, tải mẫu tại đây,
Bước 2: Chọn nút "Nộp đơn" bên trên và làm theo hướng dẫn.
Bước 3: Sau khi hoàn tất bước ứng tuyển, nếu đã ứng tuyển thành công, Bạn sẽ nhận được Thư xác nhận ứng tuyển thành công từ LOTTE Finance. Vui lòng đọc email để nắm các thông tin hướng dẫn tuyển dụng tại LOTTE Finance.
Chúc Bạn Sức khỏe và Thành công.
Head of Solution & Quality Assurance
1. Enterprise & Solution Architecture
- Define, maintain, and communicate the enterprise architecture roadmap aligned with business and technology strategy.
- Oversee solution architecture design across application domains, ensuring consistency, scalability, and reusability.
- Promote and enforce modern architectural principles, including microservices, API-first, cloud-native, and event-driven architectures.
- Govern technology standards, reference architectures, design patterns, and architectural best practices.
- Evaluate emerging technologies and recommend adoption where they deliver clear business value.
- Establish and operate architecture governance forums, design review processes, and approval mechanisms.
2. Business Analysis & Demand Management
- Establish standards, tools, templates, and best practices for business analysis across the organization.
- Oversee the elicitation, documentation, validation, and management of business requirements and user stories.
- Ensure effective translation of business requirements into solution designs in close collaboration with architecture, product, and technology teams.
- Manage scope, prioritization, and end-to-end traceability of requirements across projects and programs.
3. Quality Assurance & Testing
- Define and enforce QA strategy, methodologies, and quality standards across all technology initiatives.
- Oversee the full testing lifecycle, including functional, performance, security, automation, and UAT.
- Drive the adoption and continuous improvement of test automation frameworks to enhance efficiency and reduce time-to-market.
- Establish and monitor quality metrics and KPIs to continuously improve product and delivery quality.
4. Security, Compliance & Risk Management
- Ensure technology solutions comply with regulatory and industry standards (e.g. ISO, PCI DSS, and local financial regulations).
- Ensure systems are secure, resilient, and meet defined performance and availability SLAs.
- Identify, assess, and manage risks related to architecture decisions, technical debt, and quality issues.
5. Leadership & Stakeholder Management
- Lead, mentor, and develop enterprise architects, solution architects, business analysts, and QA professionals.
- Collaborate closely with business leaders, CIO, and functional heads to align technology initiatives with organizational objectives.
- Build and maintain strong relationships with internal stakeholders, technology vendors, partners, and regulators.
Head of Data Analytics & AI
1. Data, Analytics & AI Strategy
- Define and drive the enterprise-wide Data Analytics & AI strategy aligned with overall business objectives.
- Promote and embed a data-driven culture across all levels of the organization.
- Identify and prioritize opportunities to apply Advanced Analytics and AI to generate business value, operational efficiency, and competitive advantage.
- Oversee the design, implementation, and governance of enterprise data platforms, including data lakes, data warehouses, and analytics tools.
2. Data Platform & Analytics Enablement
- Lead the development of dashboards, management reporting, and self-service analytics capabilities.
- Ensure data quality, integrity, and compliance with applicable regulations (e.g., GDPR, local banking and financial regulations).
3. AI/ML & Advanced Analytics
- Lead the research, development, and deployment of machine learning models, natural language processing, computer vision, and other AI techniques.
- Partner with business functions (e.g., Risk, Credit Scoring, Customer Engagement, Fraud Detection, Operations) to design and implement AI-driven use cases.
- Build and scale MLOps capabilities to ensure robust model lifecycle management, monitoring, and continuous improvement.
4. People, Stakeholder & Vendor Management
- Lead, mentor, and develop high-performing teams of Data Scientists, Data Engineers, and Analysts.
- Collaborate closely with the CIO and senior business leaders to translate business challenges into scalable Data & AI solutions.
- Manage vendor relationships and evaluate emerging technologies, tools, and strategic partnerships.
5. Governance, Risk & Compliance
- Establish and maintain data governance and AI governance frameworks, ensuring ethical and responsible AI practices.
- Ensure compliance with data security, privacy, and data usage regulations.
- Identify and manage risks related to AI adoption, including model bias, explainability, and accountability.
6. Other tasks as assigned by the manager.
Education
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related discipline; PhD is a strong advantage.
Experience
- At least 8 years of experience in data, analytics, or AI-related roles, including exposure to enterprise architecture, business analysis, and quality assurance; with a minimum of 5 years in leadership or people management positions.
- Proven experience leading and scaling AI/ML initiatives in a commercial environment, preferably within financial services, fintech, or consumer-oriented industries.
- Strong track record of delivering measurable business outcomes through data-driven, analytics, and AI-powered solutions.
- Demonstrated expertise in enterprise architecture frameworks (e.g. TOGAF, Zachman) and modern technology architectures, including cloud-native, microservices, API-led, and event-driven models.
- Solid understanding and hands-on application of business analysis frameworks and practices such as BABOK, Agile BA, Lean, and Design Thinking.
Skills & Professional Competencies
- Advanced expertise in big data platforms, cloud technologies (AWS, Azure, GCP), and modern data & AI architectures.
- Strong knowledge of data governance, AI ethics, privacy, and regulatory compliance requirements, particularly in regulated environments.
- Excellent leadership, stakeholder management, and communication skills, with the ability to bridge business strategy and advanced technology solutions.
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Hà Nội, Hồ Chí Minh
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