Mox Bank is looking for a Data Scientist Lead -Data to join our Data team, to Provide data science leadership and expertise to effectively drive data driven decision making,superior analytics and machine learning use cases across the bank.
Provide data science leadership and expertise to effectively drive data driven decision making, superior analytics and machine learning use cases across the bank.
Work with Head of Data to design, prioritize and roadmap key data science and analytics projects.
Coach, mentor and develop high performing data scientists & motivate the team with clear, elevating goals.
Collaborate closely with business and product teams across the bank to identify and maximise opportunities from data.
Be a hands-on leader of a team of data scientists and data analysts in executing data science projects across different functions in the bank.
Establish standards for code quality, analysis, documentation, visualizations and data driven decision making.
Build modern, automated, cloud native tools and infrastructure for data science.
Conducting post-mortems and promoting continuous improvement.
Coordinate with the data science team to organize data literacy sessions for non-technical stakeholders in the bank.
Play a leading role in interviewing, hiring and supporting new data scientists.
5+ years of experience delivering value-adding data science and analytics initiatives in a business setting. Ideally, your experience will include financial institutional experience.
Proven experience in a similar leadership role with excellent communication and organizational skills.
Demonstrable hands-on programming knowledge in Python/R and SQL.
Solid background in machine learning theory; ranging from simple linear models, to GDBT to deep learning; and the corresponding frameworks for their implementation.
Experience applying statistics in the business decision making, through experimentation theory and causal inference.
Experience and technical knowledge of a broad range of BI tools, machine learning algorithms and web-based/cloud deployment of models.
Excellent communication and presentation skills, and an ability to translate technical methods and findings to a non-technical audience.
Proven experience building solutions using cloud services on AWS/Azure/Google Cloud.
MLOps experience using either established platforms for ML delivery (eg MLFlow) or using orchestration tools (eg Apache AirFlow, Luigi).
Practical knowledge with Git flow, Trunk and GitHub flow branching strategies.
Strong understanding and practice in Agile/Lean projects SCRUM, KANBAN etc.