Senior Data Scientist

📋 Description

• • As a Senior Data Scientist at Tide Platform Limited, you will be at the forefront of combating financial crime by developing and implementing sophisticated machine learning and statistical models. You will join the dedicated Risk & Fraud Team, a critical function within Tide, focused on protecting our rapidly growing global SME member base from evolving fraud threats.
• • Your primary responsibility will be to design, build, and deploy advanced ML/Statistical models that predict, prevent, and mitigate various fraud typologies. This involves a deep focus on optimizing costs and reducing overall risk exposure through intelligent data-driven solutions.
• • You will tackle complex challenges involving highly imbalanced and large datasets, which are characteristic of the financial crime domain. This requires a strong understanding of advanced techniques for data management, feature engineering, and model development tailored to such data characteristics.
• • A key aspect of this role is building adaptive systems. You will be responsible for creating and maintaining models that can quickly learn and adapt to new and emerging fraud patterns and tactics, ensuring our defenses remain robust against sophisticated adversaries.
• • You will be instrumental in developing, optimizing, and deploying machine learning models for real-time or low-latency inference in production environments. This involves a strong understanding of MLOps principles and practices to ensure seamless integration and operation within our tech stack.
• • You will actively utilize, enrich, and contribute to our feature store ecosystem. This ensures the availability of high-quality, scalable, and relevant features that are crucial for the performance and effectiveness of our risk models.
• • Implementing and maintaining robust drift monitoring and model performance tracking systems is essential. This proactive approach ensures that deployed models remain effective, stable, and continue to deliver value over time, flagging any degradation or need for retraining.
• • Collaboration is key. You will work closely with Machine Learning Engineers to productionize models, leveraging cloud technologies like AWS or GCP. You will also partner with Business and Product teams to deeply understand their requirements, translate them into data science problems, and architect effective data product solutions.
• • You will be encouraged to explore innovative solutions, including identifying creative ways to build relevant training datasets and investigating the potential value of new data structures, such as knowledge graphs, for advanced relational fraud detection.
• • This role offers a unique opportunity to make a tangible impact on the financial health and security of millions of SMEs worldwide. You will be part of a dynamic, fast-paced environment where data science is central to the company's mission of helping SMEs save time and money.
• • You will champion agile principles, delivering value incrementally and continuously improving our fraud detection capabilities. Your eagerness to learn new methodologies and apply them directly will be highly valued.
• • The role requires a proactive and self-starting attitude, comfortable with ambiguity and taking initiative to identify opportunities and solve challenges using data. You will be empowered to drive innovation and contribute to the strategic direction of our risk and fraud mitigation efforts.
• • You will contribute to optimizing various aspects of our business, including enhancing lead quality, reducing acquisition costs, optimizing lead allocation, and improving lending outcomes for our members through data-driven insights and models.
• • This position is ideal for a seasoned Data Scientist who is passionate about applying cutting-edge ML techniques to real-world problems in the fintech space, with a strong desire to contribute to a mission-driven company that is transforming small business banking.