Ronak D. Shah

Summary

Backend Engineer with 2+ years of experience in scalable systems and 5+ years in ML/data. Proven fintech impact through automation, tooling, and risk modeling.

Experience

MerQube Inc - Backend Engineer (Jun 2023 -- Present)

• Async Portfolio API: Designed and deployed an async Python API serving 100+ indices daily with real-time portfolio validation and scheduling; enabled automation for $600k ARR in index launches
• Tax Rate Upload Service: Built a secure, extensible API for uploading and managing tax rates; improved compliance workflows and generated $60k in annual revenue
• Pluggable QC Framework: Engineered a modular QC system executing 9000 checks/day across 8000 indices, ensuring distribution integrity and accelerating pre-release validation
• File Monitoring Service: Developed a robust file monitor scanning SFTP endpoints and executing user-defined functions; integrated with Grafana and contributed $100k in annual recurring value
• Index Configuration Tool: Created a bulk configuration update API reducing operational overhead by 80%; streamlined complex index editing workflows
• Index Reporting Engine: Architected a scalable index reporting framework now supporting 6,800 indices; improved reporting latency and reduced manual intervention
• Self-Service Index Launch: Delivered backend infra for client-driven options index deployment; cut turnaround time from 1 day to under 5 minutes

Affirm Inc - ML Engineer (Oct 2021 -- Feb 2023)

• Merchant Risk API: Built and productionized a CatBoost-based API for real-time risk exposure estimation; improved loss accuracy by 20%
• Onboarding Risk Model: Designed a GBM-based fraud detection model reducing onboarding-related fraud by 10%; integrated seamlessly with merchant approval pipeline
• Graph-based Fraud Detection: Applied graph analytics to identify suspicious merchant clusters; led to a 4% reduction in financial loss

FedEx Ground - Data Engineer (Jul 2020 -- Sep 2021)

• CFO Reporting Automation: Built automated dashboards reducing manual reporting time by 50%; ensured reliability and on-time delivery of performance insights
• Weekly Metrics Pipeline: Designed a repeatable ETL pipeline for delivering weekly operations reports to stakeholders with improved data freshness

Projects

Portfolio Optimization

• Built a Flask-based tool with Clickhouse and CI/CD for portfolio optimization
• Published research paper A unified framework for fast large-scale portfolio optimization Link.

Awards & Achievements

• Award of Honor for Outstanding Academic Excellence in AMS, Stony Brook University.
• Graduate Certificate in Quantitative Finance from AMS, Stony Brook University.
• Published research paper A unified framework for fast large-scale portfolio optimization Link.

Education

MS Applied Math and Stats , Stony Brook University (GPA: 3.95/4) - Aug 2019 - May 2021

Bachelor of Technology , SVNIT Surat (GPA: 8.51/10) - Jul 2012 - May 2016

Skills

• Languages: Python, Go, SQL, JavaScript
• Frameworks / Backend: Flask, Pydantic, Clickhouse, FastAPI
• Infrastructure: Docker, AWS, Ansible, Git, OpenLens, Kubectl
• ML \& Data: Tree Models, Convex Optimization, Graph Algorithms, Data Pipelines