Lead Data Scientist

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
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.
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)
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.
Success Profile - Qualification and Experiences
Qualifications
Bachelor's degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
Work Experience
5+ 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
Experience in querying databases and using programming languages (e.g. C, C++, R, Python, Scala, SQL, Java, Tableau, R)
Experience communicating complex analysis and models across a diverse team
Experience using of data optimization (linear / non-linear) to solve constrained business problems
Understanding of Agile principles, practices and Scrum methodologies
Experience working in Agile teams to support digital transformation projects