Data Scientist Lead - Data

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.