Data Team Support Internship

Data Team Support Intern at Pezesha – an Africa‑focused fintech that’s building a holistic digital trust platform for SMEs – offers a dynamic opportunity in Nairobi for aspiring data professionals. You’ll partner with data scientists and engineers to test, validate, and monitor credit‑scoring and M‑Pesa transaction classification models, verify ETL pipelines, and document changes. The role provides hands‑on exposure to machine‑learning pipelines, Python, SQL and R while you help maintain model accuracy above 95% and ensure reliable deployments. Ideal for recent graduates or current students in data science, computer science or statistics who are eager to launch a career in financial analytics.

Pezesha means Capital enabler. We have built a holistic digital financial trust infrastructure that is on a mission to provide affordable financial services to underserved small and medium businesses (SMBs) in Sub-Saharan Africa.

The Data Team Support Intern will support both Data Scientists and Data Engineers in testing, validating, and monitoring credit scoring and transaction classification systems.

The role is designed as a hands-on learning position, where the intern will assist with model testing, feature validation, ETL checks, deployment verification, and reporting, while gaining practical exposure to machine learning models, data pipelines, and production systems.

Key Responsibilities

• Model Testing & Validation (Data Science Support)
• M-Pesa Classifier Testing
• ETL & Deployment Support (Data Engineering Support)
• Documentation & Change Tracking

Required Qualifications

• Assist in testing credit scoring models built by Data Scientists.
• Help verify the accuracy and consistency of features used in models.
• Support basic validation of model outputs across test and production environments.
• Participate in regression testing when models or features are updated.
• Support testing of the M-Pesa transaction classifier, including LLM-based classification logic.
• Assist in measuring classification accuracy and identifying misclassified transactions.
• Help track and report classifier accuracy, with a target of above 95% under supervision.
• Assist in validating ETL pipelines that feed credit scoring systems.
• Help check data accuracy, completeness, and consistency in processed datasets.
• Support testing of deployed models to ensure they run correctly after release.

Assist in documenting:

• Model and feature changes
• ETL updates
• Testing results and observations
• Maintain simple change logs and testing notes for internal reference.

Currently pursuing or recently completed a degree in:

• Data Science
• Computer Science
• Statistics
• Information Technology
• Or a related field

Basic knowledge of:

• Python and  SQL
• Strong R programming skills
• Data analysis concepts
• Machine learning fundamentals