---
title: "Ayush Tanwar - Senior Data Scientist - Gen AI & Fraud Analytics in Gurugram | Tal"
description: "Meet Ayush Tanwar, ML Engineer | GenAI, LLM Systems, RAG & LLMOps | Fraud ML based in Gurugram. AI stack includes antigravity and claudecode. Explore public work links including github."
image: "https://tal.club/meet/ayush-tanwar/share-image"
---

# Ayush Tanwar on Tal

## Headline

ML Engineer \| GenAI, LLM Systems, RAG & LLMOps \| Fraud ML

## About

Machine learning engineer working across applied machine learning, data science, and AI research\. At American Express, I develop fraud and risk models using large\-scale real\-world data, with a focus on understanding model behavior, limitations, and tradeoffs rather than emphasizing infrastructure alone\. My interests center on robustness, interpretability, error analysis, and representation learning, as well as emerging work in LLMs, retrieval\-augmented methods, and multi\-agent systems\. I aim to bridge practical impact with research\-driven rigor\.

## Location

Gurugram

## AI stack

antigravity

claudecode

## Work experience

Senior Data Scientist \- Gen AI & Fraud Analytics at American Express, May 2025 \- Present · 1 yr 4 mos, Gurugram · Hybrid, \- Built a transcript\-driven fraud risk modeling system to capture behavioral and linguistic signals not present in transaction data\. \- Engineered large\-scale NLP features and trained an XGBoost model, achieving \~25% incremental fraud coverage\. \- Trained and evaluated a FinBERT classifier to identify fraud\-related semantic and intent signals in call transcripts\. \- Developing a GenAI based reasoning and scoring pipeline, grounded in retrieved domain knowledge from curated reference documents and validated through structured ofline benchmarking and LLM\-based evaluation for phone\-based identity takeover\.

Data Scientist \- Fraud Analytics at American Express, Sep 2023 \- May 2025 · 1 yr 9 mos, Gurugram · Hybrid, \-Twin Tower Transformer to improve Fraud Coverage on underperforming segments:Transformer Model to improve Fraud coverage on underperforming segments leveraging Specific Attention\. Ideated & Evaluated a Twin\-Tower Transformer architecture to capture temporal and intra\-transactional patterns\.Improved the Recall Score at riskiest 20bps by 1\.2% with an expected annual benefit of $6MM\.Fraud Indicator \-Meta Learner: MAML\-Optimized RNN for Regional Sequence Adaptation: \- Developed a MAML\-driven RNN to learn regional and regime\-shifting sequence patterns, boosting model coverage by 10%\. \- Built a meta\-learning pipeline with fast adaptation loops enabling reliable performance on new regional/time\-variant tasks\. \- Delivered a PyTorch\-based system with stable gradient updates and fast\-weight adaptation for improved temporal generalization\.

Data Science Intern at Spry Movement App, Jun 2022 \- Aug 2022 · 3 mos, \- Worked on various areas of development focusing on GPT3 based NLP models and fine\-tuning large\-scale language models\. \- Successfully developed a web app that facilitates Automated AI content writing for Blogs and clinic descriptions\. \- The web app is consistently being used for blog writing and Search Engine Optimization

Product Development Intern at Lam Research, May 2022 \- Jul 2022 · 3 mos, Bengaluru, Karnataka, India, \- Developed an analytical model to calculate the stresses developed in deposited layers on semiconductor wafers\. \- Improved the Stoney's equation by performing simulations for various parameters in ABAQUS and achieved an accuracy of 90%\. \- Automatized the whole simulation process using Python and created a web app Stress Calculator to reduce the modeling time

Student Member at Institute of Actuaries of India, Dec 2021 \- Aug 2022 · 9 mos, Qualifed ACET and became a student member of the Institute of Actuaries of India \(IAI, Ministry of Finance\)

CAE/FEA Analyst Intern at DRDO, Ministry of Defence, Govt\. of India, May 2021 \- Aug 2021 · 4 mos, Roorkee, India, \- Worked on a project of national importance with the Department of Science and Technology \(DST\), INDO\-SRILANKAN Research Project \- Developed various origami\-based toroidal patterns and performed the deployment simulations using ABAQUS\-CAE \- Conducted detailed stress\-strain studies using ABAQUS and MATLAB to find the optimal parameters for the satellite deployment

## Education

Bachelor of Technology \- BTech, Mechanical Engineering, Indian Institute of Technology, Delhi

Heera Lal Public School

## Public links

- github: https://github\.com/Flakes342

[View the original profile](https://tal.club/meet/ayush-tanwar)

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