Jan 2024 – Mar 2025 · 1 yr 2 mos · Bengaluru

• Contributed to the development of a generic, configuration-driven fraud policy evaluation framework, enabling flexible and scalable policy management.
• Improved Python build tooling and developer productivity workflows, reducing development friction and accelerating iteration speed.
• Enhanced API abuse detection systems to support multi-cluster deployments, improving scalability and flexibility.
• Actively participated in architecture discussions, code reviews, and on-call rotations, contributing to improved system reliability and stability.

Jul 2022 – Jan 2024 · 1 yr 6 mos · Bengaluru

• Contributed to API abuse and fraud detection services by building and optimizing large-scale data processing pipelines for anomaly detection, improving detection accuracy, execution performance, and scalability.
• Developed and enhanced Spark-based infrastructure, monitoring, and debugging tooling, significantly improving system observability and operational efficiency.

Jan 2022 – Jun 2022 · 5 mos · Hyderabad

• - Worked as part of the Customer Experience and Systems Engineering (CESE) India team, developing and delivering features for iOS India.

Sep 2021 – Jan 2022 · 4 mos · Remote

• - Worked on generating predictions and explanations for business processes using graph neural networks.

May 2021 – Jul 2021 · 2 mos · Delhi, India

• Implemented modules to double the generated customer trajectories for engagement score analysis improving leads for upselling, cross-selling opportunities, and churn possibilities.
• Contributed to research methods that mitigate the false positive rate and early stopping of conclusive tests.

May 2020 – Jun 2020 · 1 mo · Rajasthan, India

• Developed an adversarial neural network for real-time anomaly detection.
• Designed a custom loss function to improve reconstruction capabilities and classification accuracy.
• This would help in bolstering emergency services and tracking down offenders.