Head of Data Science

head of data scientist
Job Purpose

• The role involves overseeing multiple products, leading a science team, and coordinating interactions with the Business Unit. The job holder offers both technical and personal guidance to the team to ensure alignment with the business roadmap and the delivery of required technical solutions.
• The job holder proactively engages in experimenting with diverse technologies, algorithms, and tools to provide solutions to the Business Unit swiftly and in accordance with scientific standards. This includes staying updated with the latest technical advancements and industry trends.

JOB DETAIL

• Assess the efficacy of proposed models and monitor business performance against data analysis models.
• Develop state-of-the-art algorithms and collaborate with machine learning and deep learning tools to provide advanced analytics solutions throughout the organization, encompassing recommendation engines, customized data models, predictive machine learning models, graph modes, etc.
• Take the lead in identifying and interpreting meaningful and actionable insights from extensive data and metadata sources.
• Evaluate processes and tools created for monitoring and analyzing model performance and data accuracy.
• Proactively initiate discussions in more than three squads to pinpoint questions and address issues related to data analysis.

• Oversee several data products and address conflicts, challenges, and evolving business requirements to ensure seamless operations at peak performance.
• Take charge of data science teams, proposing solutions to the Business Unit, aligning Key Performance Indicators (KPIs), planning resources, resolving personnel issues and project roadblocks, maintaining project timelines, and conducting post-mortem and root cause analyses. These efforts aim to help squads continually enhance their practices and ensure maximum productivity.
• Identify and promote opportunities for growth and improvement within the team.

Qualification and Experiences
Qualifications

• Possess a Master’s or PhD degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology, or any other numerical disciplines.
• Bring forth more than 13 years of relevant experience in data analysis, machine learning, deep learning model development on extensive datasets, and implementing/deploying various statistical models. Additionally, hold at least 5 years of experience in people management.
• Showcase expertise in applying machine learning and AI to address questions pertinent to the technology and finance industry.
• Bring experience in leading successful digital transformation projects within Agile teams, being involved in end-to-end planning through implementation.

#LI-JACVN
#cityhanoi