Your mission
Lead technical efforts to enhance data modeling and insights for the Mastercard Foundation partnership, helping stakeholders achieve youth employment goals. Drive the adoption of advanced methodologies to provide actionable, granular insights.
Key Responsibilities
As a Data Scientist, you will lead and oversee data-driven initiatives that support youth employment and labor market analytics in partnership with the Mastercard Foundation. You will play a key role in designing advanced data models, mentoring junior team members, and delivering actionable insights for policymakers, private sector partners, and development organizations.
Your key responsibilities include:
- Data Modeling and Advanced Analytics:
- Design, develop, and implement advanced statistical and machine learning models to forecast labor market trends and identify key employment opportunities.
- Integrate diverse datasets, including demographic, economic, and labor market data, to produce granular insights at national and subnational levels.
- Evaluate and refine existing forecasting methodologies to ensure accuracy, scalability, and relevance.
- Technical Oversight and Quality Assurance:
- Lead and guide the team in data preprocessing, validation, and analysis to ensure high-quality outputs.
- Review and enhance code quality and analytical rigor, ensuring adherence to best practices in collaborative coding (e.g., GitHub).
- Establish and maintain robust data pipelines and workflows.
- Visualization and Reporting:
- Create compelling data visualizations, dashboards, and presentations tailored to diverse audiences, including policymakers, private sector leaders, and NGOs.
- Lead the production of blogs, reports, and other publications showcasing project findings and insights.
- Stakeholder Collaboration and Capacity Building:
- Engage with partners and stakeholders to align project deliverables with strategic goals and local needs.
- Mentor junior data scientists, providing technical guidance and fostering a culture of continuous learning.
- Represent WDL at high-profile conferences, webinars, and workshops, showcasing thought leadership in data science and labor market insights.
