Data Scientist (Machine Learning, Python, English)

The RoleAs a Data Scientist, you will contribute to deep model research and rapid prototyping. You will help identify promising algorithms, craft new features, and run rigorous experiments. You'll partner with the Engineer and Operations teams to help transition successful prototypes into production-ready solutions. Your work will involve designing and deploying machine learning models to cut false positives, uncover novel spoofing vectors, and scale across multiple products.  Key ResponsibilitiesExplore multi-modal data to develop and implement machine learning models that detect location spoofing patterns.Contribute to building robust feature pipelines and monitoring dashboards to track model performance.Mine cross-product ML signals to help build composite risk scores and network-level intelligence.Research advanced techniques like graph neural nets, time-series anomaly detection, and LLMs to address emerging fraud patterns.Collaborate with engineer managers, data engineers, and other stakeholders to refine requirements and integrate models into the ML platform.Participate in code reviews and help foster best practices in experimentation and documentation.Translate model outputs into clear reports, presentations, and recommendations for the team.Document methodologies, processes, and workflows for model development and deployment. Design, develop, and maintain robust data and feature pipelines using big data technologies like Spark, Flink, and Delta Lake.Build end-to-end machine learning pipelines, encompassing data ingestion, feature engineering, model training, evaluation, and deployment, potentially using tools like MLFlow for tracking.