Chuyên gia Khoa học Dữ liệu (Data Scientist) - MSB - DT - 1M436

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• Evaluate effectiveness of proposed models and track business performance KPIs against data model.
• 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.
• 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 & ML Engineer to build complex, technical algorithms in data analytics software applications to improve work efficiency.
• 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.
• Mentor and coach junior fellows into fully competent Data Scientists.
• Identify and encourage areas for growth and improvement within the team.

• Master's degree (or higher) in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology or other Numerical Disciplines. Ph.D. degree in the field is a plus.
• Experience in querying databases, coding and statistical computer languages (e.g. Python, Scala, Java, SQL)
• 4-8 years of relevant experience in areas of data analytics, model development on large amount of data, implementing and deploying various statistical, machine learning & deep learning models such as: Simulation, GLM/Regression, Classification, Decision Trees, Random Forest, Gradient Boosted Trees, Neural Networks, Text Mining, Graph Learning, Social Network Analysis, etc.
• Experience with data processing, statistics, machine learning and deep learning tools: Numpy, Pandas, Statsmodels, Scikit-Learn, Tensorflow, Keras, Pytorch, etc.
• Experience with distributed data/computing tools: HDFS, Hive, Presto, PySpark, etc.
• Experience with visualizing/presenting data for stakeholders using: D3.js, ggplot, matplotlib, seaborn, plotly, etc.
• Experience with cloud services (AWS, GCP, Azure)
• Experience in application of machine learning and AI to questions related to the financial sector
• Experience in providing fact-based insights to drive decision-making and help senior management and other stakeholders realize enterprise value at scale
• English proficiency requirements are pursuant to MSB's policy
• Experience with communicating complex analysis and models across a diverse team
• Excellent written and verbal communication skills for coordinating across teams
• Understanding of Agile principles, practices and Scrum methodologies
• Experience working in Agile teams to support digital transformation projects

TNTalent