Tugende
JOB DETAILS:
Reports to: Senior Data Scientist
About Tugende
Tugende uses asset finance, technology, and a customer-centric model to help informal sector entrepreneurs dramatically increase their economic trajectory. Tugende’s core asset finance packages include medical and life insurance, training, safety equipment, and digital credit profiles in addition to affordable asset financing for SMEs. By helping clients grow economically and building digital track records of responsibility, we are creating a long-term ecosystem for MSMEs that will grow and thrive.
Tugende is tackling the credit gap for small businesses in Africa by enabling informal entrepreneurs to 1) own income‑generating assets, 2) build a verifiable digital credit profile, and 3) earn future growth opportunities through the Tugende digital platform. This platform includes discounts, smartphones, e‑commerce opportunities, and on‑demand credit lines. Tugende has financed 80,000+ clients and has hundreds of employees serving clients across its branches in Uganda and Kenya.
About this role
We are seeking a Junior Data Scientist (Data Scientist I) to join our Data, Analytics, and Business Intelligence team. This is a growth-focused role for individuals ready to advance their data science skills in a highly practical, fast-paced, and impact-driven environment.
You will work under the guidance of the Senior Data Scientist and alongside experienced professionals in data engineering, analytics, finance, and technology. You’ll be involved in developing machine learning models, data pipelines, reporting tools, and intelligent automation systems that directly support key functions, including Credit, Recovery, Finance, Operations, and Product.
This role is best suited for individuals who are hungry to learn, open to mentorship, and serious about building a career in applied data science. You will be challenged, but also fully supported, in your journey from foundation to impact.
1 Key responsibilities
1.1 Data Management and Engineering Support
▪ Contribute to the ongoing structuring, cleaning, validation, and optimisation of Tugende’s enterprise data in the Redshift-based Data Warehouse.
▪ Develop and maintain reusable SQL queries and data pipelines to support analytics and reporting needs.
1.2 Reporting and Dashboard Development
▪ Build and update interactive Power BI dashboards to monitor operational, financial, and credit KPIs.
▪ Automate and publish reports for month-end performance, credit risk, recovery ops, and marketing KPIs.
1.3 Machine Learning & Model Development
▪ Contribute/support to model development for:
o Credit scoring and provisioning
o Fraud detection and revenue leakage prevention
o Asset repossession prediction and asset financing behaviour modelling
o GPS geostatistics for asset tracking and client safety
▪ Participate in the deployment of ML pipelines using:
o Assist in packaging and deploying models using containerization tools such as Docker.
o Contribute to lifecycle tracking with MLFlow (or similar tools) for versioning and performance monitoring.
o Support infrastructure deployment via AWS services such as EC2, Lambda, S3, and CloudWatch, under guidance from senior team members.
▪ Ensure models are monitored and versioned appropriately for ongoing learning and improvement.
1.4 Operations Research & Optimisation
▪ Assist in the development of optimisation models to:
o Allocate assets and staff across branches
o Plan vehicle or asset maintenance and rotation
o Optimise cost-performance trade-offs in recovery and servicing
o Portfolio, revenue and risk projection Stress Testing
▪ Apply a range of OR tools and libraries (e.g., pyomo, scipy, optimise, pulp) depending on problem structure and complexity.
1.5 Generative AI & Automation Initiatives
▪ Assist in the implementation of AI Agents for:
o Underwriting and risk assessment
o Plate detection/image validation for vehicles and bikes
o Internal knowledge base querying (LLM-powered policy agents)
o Chatbots for client servicing and operations support
▪ Support senior engineers in model monitoring and maintenance
1.6 Documentation & Collaboration
▪ Document all models, pipelines, and tools using clear technical documentation standards.
▪ Work closely with business teams to understand pain points and build tailored data solutions.
▪ Assist in preparing and delivering presentations and reports to senior leadership using PowerPoint, dashboards, or interactive notebooks.
▪ Participate in internal data literacy initiatives to empower end users across departments.
2 Qualifications
2.1 Minimum Requirements
▪ Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics or related field.
▪ 0–2 years of experience in a data science, analytics, or software engineering role (internships or academic projects accepted)
▪ Relevant coursework or certifications in machine learning, data analysis, or data engineering is an added advantage.
▪ Proficiency in Python and core data science libraries: pandas, numpy, matplotlib, scikit-learn
▪ Intermediate to strong SQL skills
▪ Exposure to Power BI or other BI tools for dashboard creation
▪ Strong Excel skills and basic experience in dashboard/report automation
2.2 Preferred but Not Required
▪ Understanding of data structures, feature engineering, and model evaluation
▪ Redshift/PostgreSQL preferred
▪ Familiarity with at least one optimisation library (e.g. pyomo, pulp)
▪ Docker, MLFlow, and AWS tools
▪ Background in asset financing, lending, or fintech is a bonus
2.3 Soft Skills & Mindset
▪ Fast learner with a strong sense of accountability
▪ Ability to thrive under mentorship and feedback
▪ Strong attention to detail and a data-driven mindset
▪ Willingness to work in a competitive, high-expectation team culture
▪ Passionate about using data to solve real-world problems
