
Data Science Intern
7 days ago
**About Thunes**
Thunes is the Smart Superhighway for money movement around the world. Thunes' proprietary Direct Global Network allows Members to make payments in real-time in over 130 countries and more than 80 currencies. Thunes' Network connects directly to over 7 billion mobile wallets and bank accounts worldwide, via more than 350 different payment methods, such as GCash, M-Pesa, Airtel, MTN, Orange, JazzCash, Easypaisa, AliPay, WeChat Pay and many more.
Members of Thunes' Direct Global Network include gig economy giants like Uber and Deliveroo, super-apps like Grab and WeChat, MTOs, fintechs, PSPs and banks. Thunes' Direct Global Network differentiates itself through its worldwide reach, in-house Smart Treasury Management Platform and Fortress Compliance Infrastructure, ensuring Members of the Network receive unrivalled speed, control, visibility, protection and cost efficiencies when making real-time payments globally.
**Context of the role**
Thunes is looking for a Data Science Intern who is eager to work with a high-impact team focused on making payments seamless across borders. This role offers an opportunity to analyse and transform data into actionable insights, helping improve the accuracy and reliability of our services and inform data-driven decision-making across the organisation.
As a Data Science Intern, you'll focus on analysing transaction data, building statistical models, and developing data visualisation tools. Your work will provide insights into customer behaviour, trends in transaction volumes, and fraud patterns. In addition, you'll use generative AI to develop tools for automated data insights, assist with descriptive and predictive analysis, and generate actionable insights for business units.
**Professional Skills and Qualifications**
- Final year or recent graduate with a background in Data Science, Statistics, Mathematics, or a related quantitative field
- Familiar with basic and latest research results in data mining, with a strong understanding of statistical models, related machine learning principles, and experience working on data mining related projects
- Familiar with machine learning, deep learning and recommendation algorithms such as clustering and classification, grasping and having deep understanding in at least one of them
- Familiarity with SQL, Python, and data visualisation tools such as Tableau, Redash, or Matplotlib
- Ability to work effectively in a team and communicate data insights clearly
- Strong analytical skills with a solid grasp of statistical methods and machine learning principles
- Completed academic projects involving data analysis, statistical modeling, or machine learning
- Experience with Large Language Models (LLMs) and Transformers is a plus (e.g., Hugging Face, AutoTrain, PyTorch, PyG, OpenAI, or other relevant APIs)
- Familiarity with cloud platforms (AWS preferred) for deploying ML models is a plus
- Previous internship experience in data analysis or related fields is preferred
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