---
title: "Aditya Gautam - Advanced Data Scientist in Bengaluru | Tal"
description: "Meet Aditya Gautam, Sr. Data Scientist | ExxonMobil | University of Pittsburgh based in Bengaluru. AI stack includes claude, mcp, and openai."
image: "https://tal.club/meet/aditya-gautam/share-image"
---

# Aditya Gautam on Tal

## Headline

Sr\. Data Scientist \| ExxonMobil \| University of Pittsburgh

## About

Analytical mindset, with broad expertise in extracting valuable information from data\. Enjoy open\-ended problems, and the use of emerging technologies for solving challenging cases in a wide range of industries\. With a strong expertise in Computer Vision, Image Processing, and Machine Learning, I thrive on transforming complex data into actionable insights\. With a solid background in developing and deploying advanced algorithms, I have successfully led projects that leverage deep learning techniques to solve real\-world problems\. My experience spans across various industries, where I have implemented innovative solutions for image recognition, object detection, and pattern analysis\. I am dedicated to continuous learning and staying at the forefront of technological advancements, always eager to tackle new challenges and drive impactful results\. Recently, I have also been exploring the exciting fields of Generative AI and Large Language Models \(LLMs\), harnessing their potential to create intelligent systems that can generate human\-like text and understand natural language with remarkable accuracy\. Looking to deliver insights and provide action\-oriented solutions to complex business problems at my next data science role\.

## Location

Bengaluru

## AI stack

claude

mcp

openai

githubcopilot

Microsoft Copilot

OpenAI Playground

## Work experience

Advanced Data Scientist at ExxonMobil, Jun 2025 \- Present · 1 yr 3 mos, • Led the design and delivery of a data‑driven invoice extraction pipeline that ingests structured and unstructured documents, automates end‑to‑end processing and reduces manual entry across finance functions\. • Architected a modular extractor framework supporting AWS Textract, Bedrock Document Analysis, and Large Language Models \(LLMs\); added a template‑based extractor creation tool that cuts new‑extractor onboarding time by >70 %\. • Implemented VLM2Vec embeddings \+ unsupervised clustering for invoice classification, enabling dynamic selection of the optimal extractor and achieving a 30% reduction in processing latency\. • Built a metadata‑rich logging and storage layer on DynamoDB and S3, providing full traceability, performance dashboards, and continuous‑learning feedback loops that raise extraction accuracy by 15 % quarter‑over‑quarter\. • Integrated prompt engineering and pagination logic for LLM‑based extractors, improving extraction quality on multi‑page, complex invoices\.

Data Scientist at ExxonMobil, Dec 2022 \- Jun 2025 · 2 yrs 7 mos, • Developed and deployed a deterministic infrared image processing framework that converts raw sensor values stored in image metadata into per pixel temperature using robust mathematical models and heat transfer equations\. • Unified outputs from Fluke and FLIR cameras into a single tool that automatically generates inspection reports and feeds a furnace health dashboard with temperature trend visualizations\. • The solution runs on minimal compute and requires no training data, enabling rapid adoption\. • Business impact: generated > $2\.5 M in direct cost savings, lifted process efficiency by ≈ 80 %, and improved furnace reliability and on\-stream availability to > 95 %\. computer vision civil inspection system: • The system first classifies the material \(steel vs concrete\) using a material specific probability threshold and then routes images that surpass this confidence level to a material tailored damage type classifier\. Achieving a ≈30 % boost in work efficiency and unlocking $17 M of value

Data Scientist \(AVP\) at IndusInd Bank, Jul 2022 \- Dec 2022 · 6 mos, Gurugram, Haryana, India

Data Scientist \(Asst\. Manager\) at IFFCO Tokio General Insurance Co\. Ltd\., Apr 2021 \- Jul 2022 · 1 yr 4 mos, • Fraud Detection\. Using tree based and gradient boosting classification methods with synthetic sample generation for optimal class balance\. • Customer Segmentation\. Using K\-Means algorithm to segregate customers in groups for optimal marketing strategy and improving customer experience\. • Renewal Propensity\. Identifying customers based on the exhaustive profile which will renew their car insurance policy\. Using boosted trees the renewal rate increased by 5\-7% on avg\. as compared to last year\. • Using Image classification and detection models developed a tool for automated claims processing for private car product\.

Data Scientist at R Systems, Sep 2019 \- Apr 2021 · 1 yr 8 mos, • Developed algorithms for predictive maintenance for the machines used in manufacturing process which led to 15% increase in manufacturing efficiency\. • Made Recommendation System for an European e\-commerce client\. Based on the buying behavior of the customers, generated the likelihood scores for combinations of products being bought together\. • Customer Segmentation\. To differentiate customers into groups based on their spending patterns, ordering frequency etc\. to optimize the marketing strategies\. Which led 5% increase in overall sales within 2 months of implementing the solution\. • Anomaly Detection for a Telecom Network provider\. This solution helped the client in identifying the patterns for the unusual spikes in network usage\. • Identified key features on the calls, for a big ISP, that affect the sale of a product using binary classification with custom score optimization methods with data gathering from MicroStrategy and Hadoop data lake\. • Uplift modelling for to find out the effectiveness of agent training for call behaviors and product offerings\. • Developed deep learning model for identifying the tabular structures and other key value pairs from invoice type documents\. Made it a language agnostic solution as it utilizes CNN\.

Data Science Student Consultant at University of Pittsburgh, Sep 2017 \- Apr 2019 · 1 yr 8 mos, Pittsburgh, Projects: • Drug Interaction: Predicting drug\-drug interactions using the drug substructure, target, side effect, off label side effect, delivery methods and more features\. The dataset contained over 150 features and 2 major interaction classes \(PK\) and \(PD\) and one was categorized as unknown\. Using XGboost classifier, Random Forest, logistic regression, neural network and feature reduction methods\(LASSO, PCA\) a comparison study against labor intensive lab methods was conducted\. Jan\.2018\-Apr\.2019 • Analysis of Athletes: Analyzed the performances of amateur athletes in the Ironman championships from 2011 to 2015\. Found out which event of the race was most influential in determining the outcome using Regression and after baselining the performance metric an exponential curve was fitted to determine the deterioration constant for the performance and the age where performance equals 0 using Scipy optimize\. Aug\-Dec 2018 • Taxi Analytics: Finding out the factors affecting the fare amount for yellow cabs in NYC and suggesting an optimized strategy for drivers to improve their profits, using statistical Machine Learning \(linear and non\-linear regression, K\-NN, neural nets, PCA, SVM\) algorithms on a 1 million\+ rows dataset\. Jul\-Dec 2018 • OR Inventory: Analyzed data for current stock and inventory levels for endocrinology department and determine opportunities to reduce and/or optimize purchases and stocking levels\. Developed plans for inventory storage and improving the processes for replenishment and for inventory monitoring in collaboration with Premier Inc\. and Stryker Sustainability at Ruby Hospital WVUHS\. Aug\-Dec 2018 • Research: Assisted in the research for Methods for Surgery Duration Estimation\. Developing Prediction Bounds using the variety and distinctness of historical Surgical Data\. Classified the complexity of the procedure based on judgements from the experts and test it against one year of actual cases\. \(UPMC\) Oct\.2017\-Jun\.2018

## Education

Master of Science \- MS, Industrial Engineering, University of Pittsburgh Swanson School of Engineering

Bachelor of Technology \- BTech, Civil Engineering, Manipal Academy of Higher Education

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

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