Data Scientist (Insurance)

Job Purpose

• The job holder supervises the setup of analytical tools to generate insights for customer journeys and product enhancements using programming methods, processes and systems to consolidate and analyze unstructured, diverse Big Data sources.
• The job holder is required to take initiative in experimenting various technologies and tools with vision of creating innovative data driven insights for the business at the quickest pace possible and keep current with technical and industry developments.

Key Accountabilities (1)
Data Solutioning

• Evaluate effectiveness of proposed models and track business performance against data analysis 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, customer journeys, 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.

Key Accountabilities (2)
Data Insighting

• 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 in 3+ squads to identify questions and issues for data analysis
• Collaborate with Data Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.

Key Accountabilities (3)
Projects Management

• 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

• Mentor and coach Data Analysts into fully competent Data Scientists.
• Identify and encourage areas for growth and improvement within the tribe.

Success Profile - Qualification and Experiences
Qualifications

• Bachelor's or Master’s degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology

Work Experience

• 7+ 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 using programming languages (e.g. C, C++, R, Python, Scala, SQL, Java, Tableau, R)
• Extensive experience in building data and analytics solutions, data mining, statistical analysis and data visualization
• Experience in application of machine learning and AI to questions related to the financial markets
• 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