Avinash V. Email & Phone Number

New York, Ny, Us

New York, Ny, Us

Atlanta Metropolitan Area

Funded by PriceWaterhouseCoopers - Predictive analytics uses ML aimed at enhancing auditors' capabilities to better predict client revenue and support audit procedures while exploring the capabilities of Generative AI. • Served as technical lead. Responsibilities included overseeing PR reviews for developers, creating short and long-term roadmaps for development, mentoring new engineers, managing deployments/infra, and troubleshooting across the technology… Show more Funded by PriceWaterhouseCoopers - Predictive analytics uses ML aimed at enhancing auditors' capabilities to better predict client revenue and support audit procedures while exploring the capabilities of Generative AI. • Served as technical lead. Responsibilities included overseeing PR reviews for developers, creating short and long-term roadmaps for development, mentoring new engineers, managing deployments/infra, and troubleshooting across the technology stack. • Constructed a feature that navigates the firm’s graph db to update vertices with latest information from FRED API, increasing build time by only 2% and avoiding extra queries to db. Resulted in significant improvements to predictions from regression model due to noise reduction to the graphs' top-k search. • Mitigated application concurrency issues by ~95% by reducing read/write operations to MongoDB, resulting in seamless multi-user functionality and speeding up application run time by 10% •. Created reusable UI components in Javascript, React, HTML, and CSS, that were utilized across the codebase. •. Developed JSON supported REST API Show less

• Architected and deployed a robust log management solution for the cybersecurity team, enhancing threat detection capabilities across 17 microservices: • Created a dedicated Kafka topic and integrated Splunk forwarding to stream logs • Implemented failure protocols including request throttling, exponential backoff, and circuit breaking • Resulted in a 40% reduction in false positives and a 25% improvement in incident response time

• Helped design and implement the containerization and orchestration initiative for a suite of microservices with Docker and Kubernetes, resulting in a 20% reduction in deployment time and a 15% improvement in resource efficiency.

Duluth, Georgia

Master Of Science - Ms, Computer Science

Concentration: Machine Learning Coursework: Deep Learning

Bachelor Of Science - Bs, Computer Science

Education record