Senior Data Scientist (40000030)

Job Purpose

- The job holder proposes, initiates and manages mutliple ML projects together with business in order to address problems raised before linked to company OKRs and product enhancements using DS methods, processes and systems on unstructured, diverse Big Data sources.
- The job holder also participates in strategic deicion circles and contributes to guiding business high level and providing strategic data guidance
- The job holder is required to allocate resources, decide strategically on projects and then cascade down to leads

Key Accountabilities (1)

Data Solutioning
- Evaluate effectiveness of proposed models and track business performance KPIs against data model.
- Build cutting-edge algorithms and work with machine learning and deep learning tools to deliver advance analytics solutions across the firm including recommendation engines, customized data models, 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.

Key Accountabilities (2)

Data Insighting
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources together with business partners.
- Review processes and tools designed to monitor and analyze model performance and prediction accuracy.
- Proactively lead discussions in 3+ squads to identify questions and issues for data science
- Collaborate with Data Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.
- Know at all times your data (size, average, distributions, outliers, CR, etc) and be able to estimate model output, impact and come up with sanity checks to detect bugs (discrepancies between expectations and results)

Key Accountabilities (3)

Project Management
- Own the project, manage POs, keep everyone on track from distractions, aligned towards lowest hanging fruit and KPI
- Manage project conflicts, challenges and dynamic business requirements to keep operations running at high performance.
- Work with team leads to resolve people problems and project roadblocks, conduct post mortem and root cause analysis to help squads continuously improve their practices to ensure maximum productivity.
Talent Development
- Manage allocated team, focus on retention and growth of the scientists, personal development and KPI
- Mentor and coach junior fellows into fully competent Data Scientists.
- Identify and encourage areas for growth and improvement within the team.

Key Relationships - Direct Manager

Director, Data Science

Key Relationships - Direct Reports

NA

Key Relationships - Internal Stakeholders

Teams within the Data Office and relevant departments in the Bank

Key Relationships - External Stakeholders

Partners and vendors providing professional services

Success Profile - Qualification and Experiences

Qualifications
- Master’s degree (or higher) in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology or other Numerical Disciplines
Work Experience
- 10+ years of relevant experience in areas of data analysis, machine learning, deep learning model development on large amount of data, implementing and deploying various statistical models
- English proficiency requirements are pursuant to Techcombank's policy
- Deep experience in querying databases and coding (e.g. Python, R, Spark, Scala, SQL, Java, C, C++)
- Extensive experience in building data and analytics solutions and products, data mining and statistical analysis
- Experience in application of machine learning and AI to questions related to the financial markets
- Strategic decision taking and thinking, able to deal with very senior management, translate tech to business and vice versa
- Deep experience in Agile Software Development and has mastery of Agile principles, practices and Scrum methodologies
- Management experience, leading projects in the past, building and mentoring scientists, leading them towards success