---
title: "Kumud Joseph K. - Director & Head of Machine Learning in Bengaluru | Tal"
description: "Meet Kumud Joseph K., Data Science/Machine Learning Leader based in Bengaluru. AI stack includes claude code, cursor, and gemini."
image: "https://tal.club/meet/kumud-joseph-kujur/share-image"
---

# Kumud Joseph K\. on Tal

## Headline

Data Science/Machine Learning Leader

## About

Data Science, Machine Learning & applied AI leader with >20yrs of experience\. Led global Data Science and Engineering teams and collaborated with Product and Business stakeholders in identifying opportunities and building DS/ML solutions around it\. Expanded the team by 5X in just 18 months\. Managed 21\+ team of managers, data scientists, MLEs & analysts across different geographies\. Designed robust & scalable solutions & collaborated with different tech teams in developing end\-to\-end products\. Created roadmap for Data Science organization\. Hired, mentored and built teams from scratch and managed projects generating $MM in revenue/year Areas:\- Automation, Chatbot, Recommendation/Relevance, Demand Forecasting, A/B Experimentations, Dynamic Optimal Pricing, Product Bundling, Text Classification/NLP, Promotion Effectiveness & Planning, Sales & Pipeline Analytics, Attrition/Retention, Segmentation/Profiling, CRM, Marketing, Campaign Design & Management, Banking Frauds, Event Based Marketing, Cross\-sell/Up Sell, Anti Money Laundering etc Industries:\- E\-Commerce, Contact Center, Product/Manufacturing, Banking, Insurance, Finance, Sales & Marketing Machine Learning: \- GLMs, Tree Based Models\(Bagging & Boosting\), CF/Assoc, Clustering, SVMs, KNNs and many more\. Deep Learning: \- Transformers, Gen AI/LLMs, MLP/ANNs, RNNs Tools/Software:\- Python/Pandas, Pytorch, Pyspark, R, SAS\(Base & EM\), SQL & sql\-like\(Hive\), Databases\(Teradata,Oracle\), Hadoop \(HDFS\), Cloud \(AWS\)

## Location

Bengaluru

## AI stack

claude code

cursor

gemini

github copilot

langchain

## Work experience

Director & Head of Machine Learning at Narvar, Jan 2024 \- Present · 2 yrs 9 mos, Bengaluru, Karnataka, India, Built IRIS, fraud/risk intelligence tool \(https://corp\.narvar\.com/iris Developed Customer Identity Graph Scaled team from 0\-to\-x

AI/ML Advisor at Startups, Jun 2023 \- Present · 3 yrs 4 mos, Mentored and served as an advisor to startups, helping them to adopt AI \(including Gen AI\)

Senior Manager, Data Science at Groupon, Oct 2019 \- Apr 2023 · 3 yrs 7 mos, United States/India, Merchant's demand forecasting \- Design and managing team working on Groupon's merchant demand forecast to onboard best merchants\. Created an impact of $1\.7m in Gross Profit/year Merchant Attrition \- Design & and managing team working on merchant attrition to help building retention strategies\. Created an impact of $650k in Gross Revenue/year Product/Deal Bundling \- Design & develop deals which are redeemed together frequently and create deal combos increasing the conversion rate to \+2% Supply Density \- Leading team in bridging supply gap corresponding to customers demand in major geographies with a potential impact of $3M/year Predicting Product Category \- Using text data from Merchant Name & Deal Title SEO Keywords recommendation \- Surfacing best keywords to help Agents write deal contents during a Deal setup\. Resulted in yearly $750k incremental revenue in US Extreme Customer Experience flagging \- Based on customer chat conversation, predicting if they have had any extreme experience\. Resulted in yearly $445k savings worldwide \+ 4% increase in customer satisfaction Experimentation \- Led Groupon's experimentation team and helped different teams run their A/B experiments smoothly and efficiently Machine Learning Platform \- Oversaw and managed Groupon's first ML platform on Cloud\(AWS\)

Manager II, Data Sciences, Groupon Global Service Organisation\(Robotics & Automation\) at Groupon, Apr 2016 \- Sep 2019 · 3 yrs 6 mos, India, Expired Deals Recommendation \- Redirecting expired deals pages to closest live deal page\. Resulted in yearly $379k impact \+ indirect improving deals SEO ranking Tour Deal Recommendation \- For Upsell \(related Tour deals\) & Cross\-sell \(Goods deal\) Agent Response Prediction/AI Chatbot Response \- Predicting top response for a customer query/interaction with Groupon's Agents Search Engine via relevance \- Improving Contact center search engine using relevance Refunds Prediction \- Predicting customers who would come for refund in near\-future Customer Segmentation \- Segment customers based on wholistic view \(value, profit, behavior, experience etc\) so as to have differential treatments Campaigns propensity model \- Identify right customer for upsell with focussed efforts Advanced Analysis of Refunds/Denials Impact

Manager I, Data Sciences, Groupon APAC at Groupon, Jan 2015 \- Mar 2016 · 1 yr 3 mos, India, Nearby Deal Recommendation \-Algorithm to show best deals in customer's vicinity on Groupon Mobile App\. Performance improvement of 15%\(AU\) and 58%\(TH\) in terms of GB reported\. Additional GB of US$25k generated between Aug'15 to Oct'15 in SG Email Deal Relevance \- Set of Algorithms and business rules, which facilitate relevant deals to users/subscribers through Emails\. Test results showed 13% more conversion rate Dynamic Pricing recommendation \-Automated Pricing correction algorithm based on performance of deals on Groupon site as well as competitor’s pricing\. Testing on sample deal shows significant increase in GB by 68% and GR by 5% Product Bundling \- Product bundling algorithm to decide which products \(complementary/imperfectly competitive goods\) should be sold together

Analytics Manager, North America at Hewlett\-Packard, Mar 2010 \- Apr 2013 · 3 yrs 2 mos, Evaluating Promotional/Marketing Effectiveness using Mix Modeling Developed a pricing/discount management tool for pricing decisions\. Potential margin impact for this initiative is US$ 16\-20 million for a year projects related to IPG\-GSB Sales Team Sales Pipeline/Opportunities Win\-Rate Analysis Account Sales analysis using RFM segmentation technique US Segmentation for optimum sales force allocation

Analytics/Machine Learning Lead at Max New York Life/Satyam, Dec 2008 \- Jan 2010 · 1 yr 2 mos, Customer segmentation/value management for retention, development & win\-back strategies Policy lapsation, Agent attrition/performace, Employee Attrition/Retention models for an Indian Insurance major Customer loyalty, perception & Customer Lifetime Value Models Building one entity\-one record for customers, agents, policies

## Education

BTech, Information Technology, Indian Institute Of Information Technology allahabad

[View the original profile](https://tal.club/meet/kumud-joseph-kujur)

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