---
title: "Sankalp Sinha - Senior Data Scientist in Bengaluru | Tal"
description: "Meet Sankalp Sinha, Data Scientist||Temenos||CMI based in Bengaluru. AI stack includes claude, cursor, and langchain."
image: "https://tal.club/meet/sankalp-sinha/share-image"
---

# Sankalp Sinha on Tal

## Headline

Data Scientist\|\|Temenos\|\|CMI

## Location

Bengaluru

## AI stack

claude

cursor

langchain

langgraph

n8n

huggingface

## Work experience

Senior Data Scientist at SimplifyX, Mar 2025 \- Present · 1 yr 6 mos, Bengaluru, Regulatory Intelligence Platform: architected an end\-to\-end system automating RIM data collection and scrutiny across Medicaid, CMS, Federal Register, Transmittals, and 20\+ regulatory sources using LLM\-powered web agents and structured extraction pipelines eliminating 24 hrs/month of manual research \(≈300 hrs/year saved\)\. Document Agent: designed and built the backend for a Document Agent on the in\-house LLM orchestration platform that extracts precise field values from unstructured PDFs \(claims forms, policy docs, transmittals\) given a field name \+ description\. RAG Pipelines: implemented and productionized RAG pipelines integrating LLMs with vector databases, achieving 85%\+ reduction in hallucination and 4× faster response times on regulatory queries\. Agentic Systems & Observability: built agentic workflows using LangChain and LangGraph; deployed agents with Aegra and instrumented pipelines end\-to\-end with OpenTelemetry \(OTel\) for tracing, monitoring, and observability of LLM/GenAI applications\. Cross\-functional delivery: collaborated with the Platform team to build automated multi\-LLM workflows for document understanding and data extraction\.

Data Scientist at Temenos India Pvt\. Ltd\. — AI Business Unit, Nov 2020 \- Feb 2025 · 4 yrs 4 mos, Bangalore Urban, Pioneered RAG‑based autonomous SQL query generator: LLMs dynamically create complex SQL with natural‑language explanations; adopted across multiple banking clients and became a core differentiator in negotiations\. Built production RAG pipeline integrating a proprietary vector database with in\-house GPU\-hosted models, delivering enhanced retrieval accuracy for financial‑domain queries\. Developed a custom Named Entity Recognition engine using fine‑tuned transformer models on scarce, domain‑specific banking/regulatory documents; outperformed off‑the‑shelf SpaCy/BERT models by 18 F1 points\. Created a product‑recommendation engine with an in‑house explainable‑AI layer; deployed via FastAPI \+ Docker \+ KServe and actively supported pre‑sales efforts, helping the team secure high‑value, profitable contracts with major banks\. Led end‑to‑end NLP payment‑message flagging system for a Tier‑1 European bank using FastAPI microservices and Docker; the solution was a decisive factor in winning the client contract\.

AI Intern at Temenos, May 2019 \- Jul 2019 · 3 mos, Bengaluru Area, India, I got the opportunity to work on fraud detection in payment transactions, Explainable AI and building model for NER, with major focus on most critical aspect of Enterprise class AI \-XAI \(Explainability\)\. Further I also got to know the ABC's of RESTFUL API development\. Awarded PPO

Data Science Intern at Temenos India Pvt\. Ltd\. — AI Business Unit, May 2019 \- Jul 2019 · 3 mos, Engineered XAI layers using SHAP and LIME to interpret Fraud Detection and NER models, ensuring enterprise\-grade model transparency, trust, and regulatory compliance\.

## Education

Master of Science, Data Science, Chennai Mathematical Institute

Bachelor of Technology, Computer Engineering, BIET Jhansi

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

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