Position Overview
Position Summary
We are seeking a highly skilled Senior Data Scientist with strong expertise in machine learning and natural language processing (NLP), and the ability to apply these capabilities to credit risk modelling and decision analytics.
This role will primarily focus on technical excellence in data science, while incorporating select high-impact Decision Analytics responsibilities from day one. The successful candidate will progressively build advanced consultancy and credit decisioning skills through on-the-job training and mentorship.
This position offers the opportunity to deliver impactful, data-driven solutions for financial institutions and other partners across East Africa, driving innovation, scalability, and ethical AI practices.
Roles and Responsibilities
A. Primary – Data Science Focus (Core of the Role)
- Credit Risk & Scoring Models
- Develop and validate credit scoring models using internal, alternative, and credit bureau data.
- Monitor model performance and recalibrate to maintain predictive accuracy and compliance with regulations.
- Data Preparation & Feature Engineering
- Collect, clean, and preprocess structured and unstructured datasets (including multilingual data).
- Engineer features to improve model accuracy and ensure explainability for regulatory and client needs.
- Machine Learning & NLP Model Development
- Design, develop, and fine-tune machine learning models for classification, prediction, and segmentation.
- Implement personalization and recommendation algorithms to enhance customer engagement.
- Deployment, Monitoring & Maintenance
- Prepare models for production deployment using appropriate frameworks and infrastructure.
- Implement monitoring systems to track performance, detect drift, and trigger retraining.
- Optimize for low-resource environments (USSD, WhatsApp, lightweight mobile deployment).
- Ethical AI & Bias Mitigation
- Apply fairness, transparency, and bias detection methods during model development.
- Create explainability frameworks for client and regulatory reviews.
B. Essential Decision Analytics - (Critical, Limited Scope)
- Client Insight Translation
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- Present analytical results in clear business terms relevant to decision-making.
- Create dashboards, visualizations, and narratives for non-technical stakeholders.
- Credit Risk Solution Support
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- Support delivery of credit risk analytics projects aligned with client business needs and best practices.
- Assist in ensuring solutions meet Basel II/III and other regulatory requirements.
- Pre-Sales & Solution Proposal Input
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- Collaborate with sales teams to understand client requirements and contribute technical input.
- Support product demonstrations and proof-of-concepts for analytics capabilities.
- Business Documentation & Specifications
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- Produce technical documentation and business specifications understandable to technical and business teams.
C. Collaboration & Growth
- Cross-Team Collaboration
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- Work closely with product managers, project managers, and software engineers to integrate analytics into solutions.
- Collaborate with regional analytics teams to share knowledge and align methodologies.
- Skill Expansion in Decision Analytics
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- Engage in structured mentorship to deepen expertise in credit decisioning strategy, scorecard design, and client consulting.
- Gradually take on more strategic and client-facing responsibilities over 12–18 months.
Required Qualifications
- Experience: Minimum 5 years in data science or applied analytics (preferably in financial services).
- Technical Skills: Python, R, SQL, and machine learning libraries; experience with transformer-based NLP and credit scoring models.
- Industry Knowledge: Exposure to credit risk modelling and familiarity with regulatory frameworks (Basel II/III).
- Education: Graduate degree in Data Science, Computer Science, Statistics, Economics, Engineering, or a related numerate field.
- Soft Skills: Strong problem-solving, communication, and stakeholder engagement skills.
- Ethical AI: Understanding of fairness, bias mitigation, and responsible AI principles.
Preferred Qualifications
- Basic UX/UI understanding for chatbot conversation design.
- Data augmentation experience (to simulate financial conversations if real data is limited).
- Ability to tailor advice relevant to the financial realities of low-income women.
- Familiarity with Kenya’s local financial ecosystem
How to Apply
How to Apply
Interested and qualified candidates should submit their CV and a cover letter detailing their relevant experience (including sample projects) September 1, 2025.
Note: This RFP/RFQ does not guarantee or commit Women’s World Banking to proceeding with the above-described work. Due to the overwhelming responses, not all candidates will be contacted.
Women’s World Banking is an equal opportunity employer for all regardless of race, color, citizenship, religion, sex, sexual orientation, gender identity or expression, age, disability, veteran or reservist status or any other category protected by federal, state, or local law.
Women’s World Banking will be unable to contract with any individual who is US citizen or resident without an LLC or LP or similar structure.
About Women's World Banking
We believe in being a force for the greater good, devoted to accelerating and growing the financial inclusion of women. With rapidly changing markets, influenced by technology and social behavioral expectations, we are embarking on a new chapter to transform the way we design and implement solutions.
For over 40 years, Women’s World Banking has partnered with financial institutions, showing them the benefit of investing in women as customers. We equip these institutions with in-depth research and data driven insights to develop financial products and educational programs. While our clients are financial service providers, our mission is to engage consumers – women who are marginalized by financial systems.
Women’s World Banking and WWB Asset Management is an equal employment opportunity for all regardless of race, color, citizenship, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, veteran or reservist status or any other category protected by federal, state or local law.
