Junior Data Scientist

Pezesha is seeking a Junior Data Scientist to join its Data Team in Nairobi, Kenya, with hybrid and remote work options available. The role provides hands-on experience working with real-world financial and transactional data while supporting data analysis, reporting, data quality, experimentation and credit risk analytics in a fast-paced fintech environment.

Key Job Information

• Job Title: Junior Data Scientist
• Employer: Pezesha
• Level: Junior
• Location: Nairobi, Kenya
• Working Arrangement: Hybrid/Remote options available
• Department: Tech / Data Team

About Pezesha

Pezesha is an embedded finance company providing affordable and data-driven credit solutions to micro, small and medium-sized enterprises (MSMEs) across Africa. The company combines technology, alternative data and financial partnerships to support financing access for small businesses and financial inclusion.

About the Role

The Junior Data Scientist will support the Data Team in turning raw data into actionable insights for credit, product, operations and business decisions. The role involves working with customer behaviour, lending performance, transaction data, credit risk and operational analytics, with opportunities to contribute to machine learning and credit-scoring projects under the guidance of senior data scientists.

This is an execution-focused learning opportunity for a curious and analytical professional who is comfortable working with data and wants to build a strong foundation in data science and analytics within a fintech environment.

Core Responsibilities

Data Analysis and Reporting

• Write SQL queries to extract, clean, transform and analyse data.
• Support the preparation of recurring business and portfolio reports.
• Conduct exploratory data analysis to identify trends, patterns and anomalies.
• Support data requests from Credit, Product, Operations, Finance and other teams.
• Validate reported metrics and investigate discrepancies in data.

Credit and Portfolio Analytics

• Analyse loan repayment performance and customer behaviour.
• Analyse lending metrics including repayment rates, PAR, DPD, disbursements, collections and portfolio performance.
• Perform customer segmentation analysis.
• Support monitoring of credit risk indicators and model performance.
• Contribute ideas for improving credit scoring.

Insights and Reporting

• Respond to data and analysis requests from cross-functional teams, including Operations, Product, Finance and Credit.
• Prepare weekly and monthly reports for internal stakeholders and external lenders covering portfolio performance and borrower analytics.
• Support ad-hoc data deep dives to identify performance trends, risks and operational issues.

Model Experimentation Support

• Work with senior data scientists to prepare datasets and evaluate the performance of machine learning and scorecard prototypes.
• Participate in feature engineering, validation testing and performance tracking of classification and credit scoring models.

Documentation and Best Practices

• Maintain clear and up-to-date documentation for datasets, metric definitions, SQL queries, ETL workflows and dashboards.
• Contribute to a shared knowledge base containing SQL snippets, data dictionaries and ETL logic to support collaboration and onboarding.
• Follow and promote data quality, quality assurance and reproducibility best practices.
• Identify and document data quality issues encountered during day-to-day work.

Key Performance Indicators

• Request SLA: Deliver at least 95% of internal data requests within agreed timelines.
• Dashboard Uptime and Quality: Maintain at least 99% uptime and accuracy for key operational dashboards.
• Experimentation Support: Support and analyse at least two credit or product experiments per quarter.
• SQL Query Reusability: Develop reusable templates for at least three core reporting use cases per quarter.
• BI Tool Enhancement: Contribute to at least one new dashboard or major enhancement per quarter.
• Documentation Coverage: Maintain 100% documentation for core queries, ETLs and reports owned.
• Cross-Team Collaboration: Receive positive feedback from at least two cross-functional teams per quarter.
• Learning and Development: Demonstrate increasing independence in SQL, analytics and data science tasks.
• Data Quality: Identify and document data issues encountered in day-to-day work.

How to Apply

Interested candidates can apply through the button below.