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 deploying robust, real-time machine learning solutions. You will be an integral part of the Risk & Fraud Team, utilizing advanced statistical modeling and machine learning techniques to proactively detect, prevent, and adapt to the ever-evolving landscape of fraud threats. This role is ideal for someone who thrives on tackling complex problems, particularly those involving highly imbalanced datasets, and is driven to deliver tangible risk reduction impact within a dynamic, fast-paced environment.
• • You will champion agile principles, ensuring value is delivered incrementally and efficiently. A strong commitment to continuous learning is essential, as you will be encouraged to explore and apply new methodologies and practices directly to your work, pushing the boundaries of what's possible in fraud detection.
• • Your core responsibility will involve the design, development, and implementation of sophisticated machine learning and statistical models. These models will be crucial for predicting and preventing a wide array of fraud typologies. A key focus will be on optimizing costs and minimizing risk through the effective application of these advanced analytical tools.
• • You will master the art of handling specialized data, employing advanced techniques to manage and model large, highly imbalanced datasets that are characteristic of the fraud domain. This includes developing strategies to extract meaningful insights from data where fraudulent activities are rare but critically important to identify.
• • A significant aspect of the role involves building and maintaining adaptive systems. These systems must be capable of rapidly evolving to counter new and emerging fraud typologies, ensuring Tide remains ahead of sophisticated criminal tactics.
• • You will be deeply involved in real-time Machine Learning Operations (MLOps), focusing on the development, optimization, and deployment of ML models for real-time or low-latency inference in production environments. This requires a strong understanding of model lifecycle management and efficient deployment strategies.
• • Data and feature engineering will be a critical component of your work. You will utilize, enrich, and contribute to the feature store ecosystem, ensuring the availability of high-quality, scalable features that are essential for the performance of risk models.
• • Implementing and maintaining robust performance monitoring systems is paramount. This includes setting up drift monitoring and continuously tracking model performance to guarantee that deployed models remain effective, stable, and reliable over time.
• • Collaboration is key to success in this role. You will work closely with Machine Learning Engineers to productionize models, leveraging a modern AWS/GCP tech stack. Furthermore, you will partner with Business and Product teams to thoroughly understand their requirements and collaboratively devise data-driven solutions.
• • You will actively explore innovative solutions, including identifying creative methods to build relevant training datasets and investigating the potential value of new data structures, such as knowledge graphs, for advanced relational fraud detection.
• • The role also involves contributing to the optimization of the sales funnel by identifying opportunities to enhance lead quality, reduce acquisition costs, optimize lead allocation, and improve the likelihood of successful lending outcomes for Tide's members, demonstrating a broad impact across the business.
• • You will be instrumental in driving data-informed decisions that directly contribute to Tide's mission of helping SMEs save time and money, thereby enabling them to focus on their core business activities.