Data Scientist, Transak

• This role is ideal for someone who is deeply analytical, enjoys solving complex problems, and wants to make a tangible impact through data
• We’re looking for someone who is deeply analytical, a self‑learner, and capable of working autonomously:
• Minimum 2 years of professional experience in data science, analytics, or a closely related role
• STEM degree from a top‑tier university (e.g., Mathematics, Computer Science, Engineering, Physics, Statistics)
• Exceptional problem‑solving skills and ability to think independently
• Strong programming skills in Python (Pandas, NumPy, etc.)
• Experience querying and working with large databases
• Proficiency in Tableau or other visualisation tools
• Ability to build data‑driven tools and automation workflows
• Strong communication skills, with the ability to explain technical concepts to non‑technical stakeholders

Desirable

• As a fast-growing fintech company, we thrive on data-driven decisions, and we’re looking for a highly intelligent, self-motivated Data Scientist to join our data team
• You will work cross-functionally, supporting various departments while also pioneering new data-driven products and internal tooling
• As a Data Scientist, you will be a core member of Transak’s centralized data team. You will extract insights, build dashboards, optimize business performance, and drive data automation. Beyond supporting different teams (Product, Operations, Sales, Liquidity, Risk, etc.), you will play a key role in developing new data products and tooling that enhance our platform’s efficiency and intelligence
• This is a high-ownership role—we expect you to be proactive, constantly learning, and thinking about how to push the boundaries of what’s possible with data
• Data Exploration & Analysis: Query, clean, and analyze data from large datasets (e.g., MongoDB) to uncover insights and drive decision‑making
• Data‑Driven Product Development: Pioneer new internal data tools and workflows that enhance efficiency across the company
• Data Visualization: Build dashboards and reports using Tableau and other visualization tools to communicate key findings
• Automated Reporting & Tooling: Develop Python‑based scripts and pipelines (using Pandas, NumPy, etc.) to streamline data processes
• Cross‑Departmental Support: Work closely with Product, Risk, Growth, and Operations teams to deliver data solutions that impact business performance
• Scalability & Efficiency: Identify inefficiencies in data workflows and develop scalable solutions to improve reporting and analytics