Job Purpose
- The job holder also participates in strategic deicion circles and contributes to guiding business high level and
- The job holder proposes, initiates and manages mutliple ML projects together with business in order to address problems raised before linked to company OKRs and product enhancements using DS methods, processes and systems on unstructured, diverse Big Data sources.
providing strategic data guidance
- The job holder is required to allocate resources, decide strategically on projects and then cascade down to leads
Key Accountabilities (1)
Data Solutioning
- 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.
- 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, etc.
- Evaluate effectiveness of proposed models and track business performance KPIs against data model.
Key Accountabilities (2)
Data Insighting
- Collaborate with Data Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.
- Review processes and tools designed to monitor and analyze model performance and prediction accuracy.
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources together with business partners.
- Know at all times your data (size, average, distributions, outliers, CR, etc) and be able to estimate model output, impact and come up with sanity checks to detect bugs (discrepancies between expectations and results)
- Proactively lead discussions in 3+ squads to identify questions and issues for data science
Key Accountabilities (3)
Project Management
- 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
- Identify and encourage areas for growth and improvement within the team.
- Own the project, manage POs, keep everyone on track from distractions, aligned towards lowest hanging fruit and KPI
- Manage project conflicts, challenges and dynamic business requirements to keep operations running at high performance.
- Manage allocated team, focus on retention and growth of the scientists, personal development and KPI
- Mentor and coach junior fellows into fully competent Data Scientists.
