Raising The Village is hiring a Data Scientist to play a pivotal role in designing, developing, and deploying a computer vision system that transforms how we assess program compliance and household adoption across last-mile communities. This role sits within the Predictive Analytics / VENN department and is central to our image-based evaluation rollout, a key pillar of the broader WorkMate AI ecosystem.
What You'll Do
- Research, design, and implement image classification and object detection models (including YOLO-based architectures) for automated adoption assessment across RTV program domains.
- Build and maintain end-to-end ML training, validation, and test pipelines ensuring model accuracy and generalizability to field conditions in low-resource environments.
- Optimize models for edge deployment in environments with limited connectivity, including TensorFlow Lite integration for mobile and offline use cases.
- Design and manage image data collection protocols and annotation workflows to produce high-quality labeled datasets.
- Integrate image metadata and classification outputs with the RTV data warehouse for correlation with household progression and adoption metrics.
- Develop automated adoption classification outputs that map to RTV's binary and weighted adoption scoring frameworks.
- Conduct structured experiments to benchmark model performance across deployment contexts, applying Weights & Biases for experiment tracking.
- Build and document RESTful APIs to expose model predictions to WorkMate and other consuming field applications.
- Maintain clear documentation of model architectures, preprocessing pipelines, evaluation metrics, and versioning practices.
What We're Looking For
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics (Statistical computing), or a related quantitative field.
- 3+ years of hands-on experience in machine learning and computer vision, with a demonstrable portfolio of deployed models.
- Proficiency in Python (PyTorch or TensorFlow) for deep learning model development.
- Proficiency in object detection and image classification frameworks, particularly YOLO architectures (YOLOv8 or later).
- Proficiency in data annotation tools and active learning workflows for building labeled datasets.
- Proficiency in cloud platforms, specifically AWS, for model training, storage, and deployment.
- Proficiency in SQL and familiarity with data warehouse environments (Databricks preferred) for integrating model outputs with structured household data.
- Proficiency in model deployment and MLOps practices, including CI/CD pipelines and experiment tracking with Weights & Biases or equivalent.
- Proficiency in edge deployment optimization (TensorFlow Lite, ONNX) for low-connectivity field environments.
- Experience building and documenting RESTful APIs to expose model predictions to consuming applications.
Nice to Have
- Familiarity with mobile data collection platforms (SurveyCTO, ArcGIS, Custom APPs) and field data workflows in development or humanitarian contexts.
Technical Stack
- Languages & Frameworks: Python, PyTorch, TensorFlow, YOLO (YOLOv8 or later), SQL
- Platforms & Tools: AWS, Databricks, TensorFlow Lite, ONNX, Weights & Biases, RESTful APIs
Team & Environment
The role sits within the Predictive Analytics / VENN department, which is the data and technology backbone of the organization. You will report to the Senior Data Scientist.
Work Mode
This is a local-country based position located in Mbarara.
Raising The Village is committed to Equity and Inclusion in the workplace and is proud to be an equal opportunity employer.
