DEADLINE: 31/05/2025

Data Scientist

Full-time

Tugende is hiring a Data Scientist to join the Data, Analytics, and Business Intelligence team. This role is ideal for growth-oriented individuals eager to develop their data science skills in a practical, fast-paced, and impact-driven environment. You will work under the guidance of the Senior Data Scientist and collaborate with professionals in data engineering, analytics, finance, and technology. The role involves developing machine learning models, data pipelines, reporting tools, and automation systems to support critical functions like Credit, Recovery, Finance, Operations, and Product.

This position is suited for candidates who are:

Eager to learn and open to mentorship.
Committed to building a career in applied data science.
Ready to tackle challenges with full support from the team.

1. Key Responsibilities

1.1 Data Management and Engineering Support

Contribute to structuring, cleaning, validating, and optimizing 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 operations, and marketing KPIs.

1.3 Machine Learning & Model Development

Support the development of models for:
- Credit scoring and provisioning.
- Fraud detection and revenue leakage prevention.
- Asset repossession prediction and asset financing behavior modeling.
- GPS geostatistics for asset tracking and client safety.
Participate in deploying ML pipelines using:
- Containerization tools like Docker for packaging and deployment.
- MLFlow (or similar tools) for versioning and performance monitoring.
- AWS services (e.g., EC2, Lambda, S3, CloudWatch) under senior team guidance.
Ensure models are monitored and versioned for continuous improvement.

1.4 Operations Research & Optimization

Assist in developing optimization models to:
- Allocate assets and staff across branches.
- Plan vehicle/asset maintenance and rotation.
- Optimize cost-performance trade-offs in recovery and servicing.
- Perform portfolio, revenue, and risk projection stress testing.
Use optimization tools/libraries (e.g., Pyomo, SciPy, PuLP) based on problem complexity.

1.5 Generative AI & Automation Initiatives

Support implementation of AI Agents for:
- Underwriting and risk assessment.
- Plate detection/image validation for vehicles and bikes.
- Internal knowledge base querying (LLM-powered policy agents).
- Chatbots for client servicing and operations support.
Assist senior engineers in model monitoring and maintenance.

1.6 Documentation & Collaboration

Document models, pipelines, and tools using clear technical documentation standards.
Collaborate with business teams to understand pain points and deliver tailored data solutions.
Prepare and deliver presentations/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 a 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 a plus.
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.
Experience with Redshift/PostgreSQL is preferred.
Familiarity with optimization libraries (e.g., Pyomo, PuLP).
Knowledge of 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.
Thrives 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.

CLICK HERE TO APPLY

About Tugende

Industry: Data Analysis

Location: Kampala, Uganda

Tugende leverages asset finance, technology, and a customer-centric model to empower informal sector entrepreneurs in Africa, significantly boosting their economic trajectory. Tugende’s core offerings include: Asset finance packages with medical and life insurance, training, safety equipment, and digital credit profiles. Support for SMEs to own income-generating assets, build verifiable digital credit profiles, and access growth opportunities via the Tugende digital platform (e.g., discounts, smartphones, e-commerce, and on-demand credit lines). Operations in Uganda and Kenya, serving over 80,000 clients with hundreds of employees across branches. Mission: Address the credit gap for small businesses by fostering economic growth and creating a long-term ecosystem for MSMEs.