Summary
Date Posted: Wednesday, February 05 2025, Base Salary: Not Disclosed

JOB DETAILS:
About Raising The Village:
At Raising The Village (RTV), we are dedicated to eradicating ultra-poverty in Sub-Saharan Africa. As a dynamic and rapidly growing international development organization, we have assembled a team of over 200 passionate individuals in Uganda, alongside an additional 12+ professionals in North America, and 14+ in Rwanda, with more expansion based in the Sub-Saharan Region. Together, we're committed to elevating communities out of ultra-poverty by implementing innovative solutions and leveraging advanced data analytics to drive impact. To date, our holistic approach has positively impacted over 1M+ lives, and we're poised to reach even greater milestones, aiming to reach over 1,000,000 participants annually by 2027. Our journey of growth and success is made possible by the invaluable support of our global partners who share our vision and belief in sustainable change. Learn more about our impactful programs at www.raisingthevillage.org 

Job Summary:
The Data Scientist will play a pivotal role within the PEAL department, leveraging advanced analytics and artificial intelligence to drive data-informed decision-making and enhance program effectiveness. This position requires collaboration with internal and external teams to integrate data-driven insights into program strategies, supporting Raising The Village's mission to eradicate ultra-poverty in Sub-Saharan Africa.

Responsibilities:
• Data Exploration & Analysis: Collect, clean, and preprocess data from various sources. Perform exploratory data analysis (EDA) to uncover patterns and trends supporting program interventions.
• Model Development & Deployment: Design, develop, and implement production-ready machine learning models.
• AI Systems Development: Develop and maintain retrieval-augmented systems, implement robust unit tests, and refactor existing codebases for improved performance.
• API Development for Model Serving and Data Processing: Design and implement APIs to facilitate efficient model deployment and data handling, ensuring seamless integration with existing systems.
• Data Visualization & Reporting: Create compelling visualizations, dashboards, and detailed reports to communicate insights to both technical and non-technical stakeholders.
• MLOps & Deployment: Handle end-to-end model deployment, including monitoring and maintenance in production environments. Implement CI/CD pipelines for ML models.
• Research & Innovation: Stay current with the latest developments in AI/ML, conduct R&D to improve methodologies, and implement cutting-edge solutions where appropriate.

Qualifications and Skills:
• Advanced degree in Data Science, Computer Science, Statistics, Mathematics, Software Engineering, Computer Engineering, or a related field.
• 4+ years of experience in data science and machine learning engineering.
• Strong programming proficiency in Python for AI/ML development, including data science libraries (NumPy, pandas, scikit-learn).
• Experience with deep learning frameworks (TensorFlow, PyTorch) and ML model deployment.
• Demonstrated experience with generative AI and large language models, including RAG systems and vector search implementations.
• Experience with front-end technologies (React) and RESTful API development.
• Experience with MLOps tools (Docker, Kubernetes), CI/CD pipelines, and cloud platforms (AWS, GCP, Azure).
• Strong knowledge of SQL and NoSQL databases, including vector databases (e.g., Qdrant, Pinecone, Weaviate).
• Expertise in data visualization tools (Tableau, Power BI) and advanced prompt engineering techniques.
• Proficiency with version control systems (Git) and data pipeline/ETL processes.
• Strong analytical thinking and problem-solving abilities with a full-stack mindset.
• Outstanding communication and training skills for both technical and non-technical audiences.
• Experience in participatory research within last-mile communities is an advantage.
• Self-motivated team player with the ability to manage multiple priorities.

Work Hours: 8

Experience in Months: 48

Level of Education: Bachelor Degree

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• Interested and qualified? Click here to apply

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