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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.
Headquartered in Singapore, Thunes has offices in 12 locations, including Barcelona, Beijing, Dubai, London, Manila, Nairobi, Paris, Riyadh, San Francisco, Sao Paulo and Shanghai. For more information, visit: https://www.thunes.com/
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
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Industry:Other
Job Type:Permanent Job
Date Posted: 08/11/2024
Job ID: 99659177