👋 Hello, I'm

Ronak D. Shah

Backend Engineer

Scalable Systems ML/Data Fintech

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.

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Years Backend Experience

Years ML/Data Experience

100%

Fintech Impact

Professional Experience

A journey through impactful roles in fintech and data science

Software Engineer - Backend

MerQube Inc

Jun 2023 -- Present

Leading development of scalable systems and innovative solutions in fintech and data science.

Async Portfolio API

Architected async Python API for validating 100+ portfolios/day; enabled $600k ARR by automating index portfolio management

Index Platform API

Designed and scaled production-grade FastAPI backend on K8s, improving developer and operations experience on working with index code

Real Time System

Led real-time infra upgrades using time-based autoscaling and safe rollovers, improving system uptime and reducing deployment costs

File Monitoring Service

Built resilient file monitor service with user-defined workflows and integrated prometheus metrics and Grafana alerts, adding $100k in ARR

Multi Asset Framework

Engineered object oriented framework with abstract interfaces and modular components for multi-asset indices; enabled reusable, type-safe index development

Index Reporting Engine

Engineered scalable, standardized reporting pipeline for 6,800+ indices. Implemented robust data validation using pydantic to ensure accuracy and reliability

Self-Service Index API

Delivered client-facing API for index creation and backtesting; enabled near real-time onboarding of custom index strategies

Technologies & Skills

Python SQL Kubernetes ML DevOps

Software Engineer - Quantitative Risk

Affirm Inc

Oct 2021 -- May 2023

Leading development of scalable systems and innovative solutions in fintech and data science.

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

Technologies & Skills

Python SQL Kubernetes ML DevOps

Software Engineer - Data Science

FedEx Ground Inc

Jul 2020 -- Sep 2021

Leading development of scalable systems and innovative solutions in fintech and data science.

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

Technologies & Skills

Python SQL Kubernetes ML DevOps

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Skills & Technologies

A comprehensive toolkit for building scalable, data-driven applications

Core Technologies

Python

Backend development, data science, and automation

SQL

Database design, optimization, and analytics

Kubernetes

Container orchestration and cloud infrastructure

Technical Expertise

Backend Development

95%

Expert-level backend development with focus on scalable APIs and microservices

Technologies:

FastAPI Flask Django Pydantic SQLAlchemy

Key Achievements:

Built production APIs handling 100+ portfolios/day
Scaled FastAPI backend on Kubernetes
Implemented async processing for real-time data

Data Science & ML

90%

Advanced machine learning and data science with focus on fintech applications

Technologies:

CatBoost GBM Graph Analytics Scikit-learn Pandas

Key Achievements:

Improved risk model accuracy by 20%
Reduced fraud by 10% with ML models
Applied graph analytics for fraud detection

Cloud Infrastructure

85%

Comprehensive cloud infrastructure and DevOps expertise

Technologies:

AWS Docker Kubernetes Ansible Prometheus

Key Achievements:

Implemented time-based autoscaling
Reduced deployment costs with infrastructure optimization
Built resilient monitoring systems

DevOps & CI/CD

80%

Modern DevOps practices and continuous integration/deployment

Technologies:

Git CI/CD Monitoring Grafana Prometheus

Key Achievements:

Automated deployment pipelines
Integrated comprehensive monitoring
Improved system uptime and reliability

Domain Knowledge

Fintech & Quantitative Finance

Expert

Deep expertise in financial technology and quantitative modeling

Key Areas:

Portfolio Optimization Risk Modeling Index Management Financial APIs Real-time Trading Systems

Notable Achievements:

Generated $600k ARR through portfolio automation
Managed 6,800+ indices with automated reporting
Built real-time risk exposure estimation systems

Machine Learning & AI

Advanced

Advanced machine learning with focus on practical business applications

Key Areas:

Predictive Modeling Fraud Detection Graph Analytics Automated Decision Systems Model Productionization

Notable Achievements:

Deployed ML models in production environments
Applied graph algorithms for fraud detection
Built automated risk assessment systems

Scalable Systems Architecture

Expert

Expertise in designing and building high-performance, scalable systems

Key Areas:

Microservices Architecture High-Performance APIs Distributed Systems Real-time Processing System Optimization

Notable Achievements:

Architected async portfolio validation systems
Scaled APIs to handle high-throughput workloads
Implemented resilient file monitoring services

Data Analytics & Business Intelligence

Advanced

Comprehensive data analytics and business intelligence expertise

Key Areas:

Business Intelligence Reporting Automation Data Pipelines Performance Analytics Stakeholder Reporting

Notable Achievements:

Reduced manual reporting time by 50%
Built automated ETL pipelines
Delivered real-time performance insights

Key Achievements

$600k

ARR Generated

20%

Accuracy Improvement

6,800+

Indices Managed

Featured Projects

Innovative solutions and research that demonstrate my technical expertise

Portfolio Optimization

Built a Flask-based tool with Clickhouse and CI/CD for portfolio optimization

Flask Clickhouse CI/CD Portfolio Optimization

Research Publication

A unified framework for fast large-scale portfolio optimization

Read Paper

Risk Modeling API

CatBoost-based API for real-time risk exposure estimation with 20% improved accuracy

CatBoost API ML

Graph Analytics

Graph-based fraud detection system identifying suspicious merchant clusters

Graph Analytics Fraud Detection Python

Real-time Infrastructure

Time-based autoscaling and safe rollovers improving system uptime

Kubernetes Autoscaling DevOps

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Education & Credentials

Academic foundation that drives my technical expertise and problem-solving approach

MS Applied Math and Stats

Stony Brook University

Duration

Aug 2019 - May 2021

GPA

3.95/4

Academic Excellence

Bachelor of Technology

SVNIT Surat

Duration

Jul 2012 - May 2016

GPA

8.51/10

Awards and Achievements

Award of Honor for Outstanding Academic Excellence in AMS, Stony Brook University

Graduate Certificate in Quantitative Finance from AMS, Stony Brook University

Let's Connect

Ready to discuss opportunities or just want to say hello?

Email

Let's start a conversation

roshah2023@gmail.com

Location

Based in

San Francisco, CA

Phone

Call me anytime

(412) - 447 - 1666

Professional network

Connect on LinkedIn

Website

More about me

Visit Website

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