Job Purpose
- The job holder manages multiple data science products by leading the data science team and coordinating closely with Business Units (BUs). She/he provides both technical and people leadership to ensure the alignment with the business roadmap and the delivery of high-quality solutions. quality technical solutions.
- The job holder is expected to have the ability to develop and drive a vision and strategy for Data Science that is fully aligned with the organization's AI strategy, ensuring that advanced analytics and AI capabilities effectively serve diverse business areas.
- The job holder proactively experiments with emerging technologies, algorithms, and tools to deliver innovative solutions to BUs at the fastest possible pace while maintaining scientific rigor and staying current with industry and technological advancements.
Key Accountabilities (1)
AI and Data Solutions:
- Evaluate effectiveness of proposed models and track business performance against data analysis models.
- Build cutting-edge algorithms and work with machine learning and deep learning tools to deliver advanced analytics solutions across the firm including recommendation engines, customized data models, predictive machine learning models, graph modes, etc.
- Drive application of machine learning and big data techniques across different journeys and squads.
- Manage, execute, and review complex data science projects in an agile manner and in compliance with internal regulatory requirements.
- Maintain a thorough understanding of current AI-related technologies including GenAI, Agentic AI, prompt engineering, LLM fine tuning and distillation, Retrieval Augmented Generation (RAG), and agentic workflows and apply this expertise to design and deliver next generation AI solutions.
Key Accountabilities (2)
Data Insights:
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.
- Review processes and tools designed to monitor and analyze model performance and data accuracy.
- Proactively lead discussions to identify questions and issues for data analysis
- Collaborate with AI and Data Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.
Projects Management:
- Manage multiple data products and resolve conflicts, challenges and dynamic business requirements to keep operations running at high performance.
- Lead involved data science teams to propose solutions to BU, align KPIs, plan resources, resolve people problems and project roadblocks, keep project on track, conduct post-mortem and root cause analysis to help squads continuously improve their practices to ensure maximum productivity.
- Identify and encourage areas for growth and improvement within the team.
Key Accountabilities (3)
People Management
- Oversee human resources planning and execution (headcount & costs) of their function/ sub- function
- Attract, onboard and retain the right talents for a high- performing team
- Establish and communicate sub- function/ function and individual KRAs/ KPIs, goals, action plan, expectations and results to reporting line
- Manage sub- function/ function performance & provide feedback regularly (following the annual performance management cycle)
- Define team's capability requirements and enable team member's professional and personal development through capability assessment, training, coaching & feedback, mentoring, etc.
- Motivate and recognize team members contributions towards the team's shared goals
- Responsible for developing talents within the function/ sub-function
- Act as a role model and promote corporate culture at function/ sub- function level
- Understand and communicate relevant HR offerings to team members.
Key Relationships - Direct Manager
Head of Data & Analytics
Key Relationships - Direct Reports
- Senior Data Scientist
- Data Scientist
Key Relationships - Internal Stakeholders
Partners providing professional services
Success Profile - Qualification and Experiences
Qualifications
- Master's or PhD degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information
- Technology or any other Numerical disciplines Work Experience
- 12+ years of relevant experience in areas of data analysis, machine learning, deep learning model development on large amounts of data, implementing and deploying various statistical models, 4+ years of people management experience.
- English proficiency requirements are pursuant to Techcombank group's policy
- Deep experience in querying databases and using programming languages (e.g. Python, spark, TensorFlow, Scala, SQL, C, C++, Java)
- Extensive experience in building data and analytics solutions, data mining, statistical model building, predictive modeling
- Experience in application of machine learning and AI to questions related to tech and finance industry
- Experience in providing fact-based insights to help senior management and other stakeholders realize enterprise value at scale
- Deep experience in Agile Software Development and has mastery of Agile principles, practices and Scrum methodologies
- Experience working in Agile teams to lead successful digital transformation projects, involved in the end-to-end planning to implementation
