---
title: "Amogh Makam - Data Scientist 1 in Tumkur | Tal"
description: "Meet Amogh Makam, Data Scientist @ Epsilon | VIT ’24 based in Tumkur. AI stack includes anthropic apis, claude code, and claude. Explore public work links including github, leetcode, and portfolio-zeta-amber-69.vercel.app."
image: "https://tal.club/meet/amogh-a-m/share-image"
---

# Amogh Makam on Tal

## Headline

Data Scientist @ Epsilon \| VIT ’24

## About

Two engineers ship the same model\. One writes "developed ML pipeline\." The other tells you what changed because of it — I'm the second kind\. I'm a Data Scientist at Epsilon, where I build production ML and GenAI systems for CPG and healthcare clients — causal inference and campaign measurement, heterogeneous uplift modeling \(Double\-ML / R\-learner CATE estimation\), and multi\-agent RAG architectures\. My daily stack: Python, PySpark, Databricks, and AWS\. The foundation came early\. I graduated with a B\.Tech in Computer Science \(Data Science specialization\) from VIT with a 9\.05/10 CGP\. Along the way I authored 2 peer\-reviewed publications \(ICMLDE 2023 / Elsevier and IEEE Engineering Informatics 2023\) and picked up certifications in Databricks, AWS, and Adobe Analytics\. What I care about most: models that survive contact with production\. Measurement that stands up to scrutiny\. GenAI systems that do real work instead of demos\. Always happy to talk multi\-agent systems, causal ML, or GenAI in production — message me here on LinkedIn\.

## Location

Tumkur

## AI stack

anthropic apis

claude code

claude

langchain

langgraph

Microsoft Copilot

## Work experience

Data Scientist 1 at Epsilon, Aug 2024 \- Present · 2 yrs 4 mos, Hybrid, Built a heterogeneous uplift modeling pipeline in PySpark/Databricks using Double\-ML/R\-learner CATE estimation on a \~2M matched\-panel CPG campaign, enabling audience\-level targeting decisions instead of single average\-lift reads Designed and shipped a multi\-agent GenAI insights system \(LangGraph/LangChain\) with router, text\-to\-SQL, RAG, and QA/verifier agents — letting non\-technical brand stakeholders query campaign data in plain English, with every numeric claim verified before delivery Diagnosed and resolved production ML reliability issues including non\-deterministic CATE outputs, label\-encoding faults, and null\-imputation bugs, stabilizing pipeline outputs for repeatable client measurement Delivered causal campaign\-measurement and propensity\-modeling analyses for CPG and healthcare clients on AWS/Databricks, translating model outputs into targeting and budget recommendations

Data Analyst at Epsilon, Feb 2024 \- Aug 2024 · 7 mos, On\-site, Analyzed large\-scale campaign datasets using PySpark and SQL on Databricks, producing measurement readouts and audience profiling reports for CPG clients Built decision\-tree segmentation and lift\-based labeling workflows that fed downstream uplift models — work that contributed to promotion to Data Scientist within 7 months

Computer Science Intern at Hindustan Aeronautics Limited, May 2023 \- Jun 2023 · 2 mos, Bengaluru, Karnataka, India, Developed a Flight Phase Detection system that detects the Phase of the Flight based on the sensor data\.

Senior Core member at Kannada Literary Association, Sep 2022 \- Apr 2023 · 8 mos, Vellore, Tamil Nadu, India

## Education

Bachelor of Technology \- BTech, Computer Science Engineering with Specialization in Data Science, Vellore Institute of Technology

Secondary High School, Mathematics and Computer Science, Deeksha Centre for learning

## Public links

- github: https://github\.com/makamamogh23\-arch
- leetcode: https://leetcode\.com/Makamamogh
- portfolio\-zeta\-amber\-69\.vercel\.app: https://portfolio\-zeta\-amber\-69\.vercel\.app/

[View the original profile](https://tal.club/meet/amogh-a-m)

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