Internship Opportunities at Cytonn Investments

Responsibilities

• Conduct research on local and global payment ecosystems, including banks, fintechs, and emerging solutions.
• Analyze local and international payment processes (including M-Pesa, card networks, crypto, stable coins, and cross-border remittances), identify key inefficiencies and gaps, and evaluate how stable coins can integrate with existing infrastructure to improve speed, cost, and accessibility.
• Assist with partner and merchant requirements: KYB/KYC documentation, due diligence questionnaires, and compliance checks.
• Engage both internal stakeholders and external partners to align operational requirements and pain points with available market solutions and capabilities.
• Document findings, process flows, and potential solution approaches.
• Support the development of business cases for new payment solutions or improvements.
• Contribute to ongoing improvements in payment processes and infrastructure.
• Track industry trends and innovations in payments and financial services.
• Collaborate with system analysts and technical teams to translate research into actionable insights.
• Any other duties that will be assigned from time to time

Requirements

• Have attained at least a B+ in KCSE (or its equivalent).
• Have graduated or are expecting to graduate with at least a Second Class Upper Honors (or its equivalent).
• Experience or familiarity with digital payments ecosystem is a strong added advantage
• Have a high tolerance for constructive criticism of their work.
• Strong research, analytical, and problem-solving skills.
• Good communication skills with the ability to engage both technical and non-technical stakeholders
• Curious, proactive, and willing to learn about financial systems and payments.
• Understanding of financial services, payments, or fintech is an added advantage.
• Ability to manage multiple tasks and meet deadlines in a fast-paced environment.

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Responsibilities

• Build, train, and evaluate machine learning models on real business datasets across service lines including investments, real estate and other services;
• Develop AI-powered applications using Python, FastAPI, and Streamlit that automate and enhance company internal workflows and client-facing services;
• Integrate and work with commercial AI APIs including OpenAI and HuggingFace to build intelligent features such as smart document processing, digital investments, client query handling, next-gen AI-powered digital marketing and recommendation systems;
• Conduct exploratory data analysis and produce clear, actionable data insights that inform business decisions across the organisation;
• Apply prompt engineering techniques to build reliable, structured AI pipelines for content generation, classification, and summarisation tasks;
• Package and deploy models using MLOps best practices including experiment tracking with MLflow, containerisation with Docker, and CI/CD pipelines with GitHub Actions;
• Conduct responsible AI audits on models assessing for bias, fairness, explainability, and data privacy compliance;
• Collaborate with the Product and Operations teams to identify AI automation opportunities and translate them into working prototypes;
• Document all models, pipelines, and applications to professional standards including model cards, data cards, and technical READMEs;
• Scope, build, and present a capstone AI project that solves a real problem
• Any other duties as may be assigned from time to time.

Requirements

• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field from a recognised university;
• Must have attained a B and above in KCSE or equivalent;
• Proficiency in Python or a clearly demonstrated ability to learn programming rapidly and independently;
• Tech-savvy mindset with demonstrable experience using AI tools such as ChatGPT or Gemini for research, analysis, or content tasks;
• Demonstrated interest in AI exemplified by actual prior project;
• Strong analytical and problem-solving skills with high attention to detail;
• Familiarity with data analysis, basic statistics, or machine learning concepts is an advantage;
• A team player willing to learn, adapt, and work with minimum supervision;
• Excellent organisation, communication, and interpersonal skills; and
• High levels of energy and enthusiasm with the ability to work under pressure and meet deadlines.