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Data Scientist

Category:  Data and Analytics Division
Job Type: 
Facility:  Data & Analytics


- The job holder advises and provides business with insights from massive amounts of structured and unstructured potential data to help shape or meet specific business objectives.
- The job holder will build data science solutions using advance machine learning and deep learning methods, recommendation engines, statistical analysis, data mining and data visualization techniques, to create solutions that enable enhanced business performance.

Key accountabilities (1)

A. Data Solutioning
- Build algorithms and work with machine learning and deep learning tools to deliver advance analytics solutions across the firm including recommendation engines, customized data models, customer journeys, graph modes, etc.
- Mine and analyze data from company’s databases to drive optimization and improvement of business strategies.
- Use predictive modelling to increase and optimize customer journey experiences, revenue generation and other business outcomes.
- Analyze data for trends and patterns and interpret the data with clear objective in mind.
- Execute and review data science projects in an agile manner and in compliance with internal regulatory requirements.
B. Data Insighting
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Interact with 1-2 squads to identify questions and issues for data analysis.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Key accountabilities (2)

Key accountabilities (3)

Key Relationships - Line Manager

Direct: Data Analytics Lead

Key Relationships - Subordinate

Direct: None

Key Relationships - Internal relationship

Teams within the Transformation Office and relevant departments in the Bank

Key Relationships - External relationship

Partners providing professional services

Success Profile - Qualification and Experiences

Bachelors degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
6 to 8 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 Techcombanks 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

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