Manu Kothari

AI Researcher

Cupertino, California, United States9 yrs 9 mos experience
Most Likely To SwitchAI Enabled

Key Highlights

  • Expert in Machine Learning and Data Science.
  • Proven track record in e-commerce optimization.
  • Strong academic background with top grades.
Stackforce AI infers this person is a Data Science expert in E-commerce with strong Machine Learning capabilities.

Contact

Skills

Core Skills

Data ScienceMachine Learning

Other Skills

TFIDFWord2VecXGBoostData AnalysisRFM AnalysisArtificial IntelligencePythonAlgorithmsData StructuresComputer VisionBig DataCloud ComputingStatisticsJavaC++

About

If you find my profile interesting, please drop a mail to manukothari@gmail.com

Experience

Apple

2 roles

Senior Machine Learning Engineer

Promoted

Oct 2021Present · 4 yrs 5 mos · United States

Machine Learning Engineer

Jun 2019Oct 2021 · 2 yrs 4 mos · United States

Georgia institute of technology

Graduate Teaching Assistant - Artificial Intelligence

Aug 2018May 2019 · 9 mos · United States

Myntra

3 roles

Associate Data Scientist

Apr 2018Jul 2018 · 3 mos · Bengaluru, Karnataka, India

  • Sentient - Analyze various multilingual customer touchpoints and aggregate all data sources to predict whether a customer interaction will lead to an escalation
  • Drove the project from conceptualization to execution as a part of Myntra Innovation Challenge '18
  • Improved the precision by 4% by using TFIDF weighted Word2Vec embeddings to classify customer call transcripts and emails as escalations resulting in ROC AUC of 0.96 for the ensemble model

Software Engineer, Data Science

Jul 2016Apr 2018 · 1 yr 9 mos · Bengaluru, Karnataka, India

  • SABRE - Smart AI Based Returns - Determining the probability of genuine return and green-channeling (pre-approve) it for pickup given a customers' purchase and return history
  • Productionized the model enabling instant doorstep refunds across 100% of Myntra returns since June '17
  • Deployed an XGBoost model (V2) having a ROC AUC of 0.82 compared to V1 with 0.67 resulting in a 13% increase in green-channeling and a drop in return on-hold (ROH) cases (38 point difference in return NPS) from 1.7% to 0.2%
  • Won the ‘Effective Tech Implementation’ of the year award at IFF ’18
  • Buyer Program - Inducing repeat purchase behavior using personalized notifications and feedcards
  • Achieved significantly higher open rates (6.5% - almost 2X) for personalized notification compared to generic (3.5%)
  • Increased browse to buy conversion from 6% to 10% resulting in 2% incremental revenue

Software Engineer Intern, Data Science

Jan 2016Jul 2016 · 6 mos · Bengaluru, Karnataka, India

  • User Segmentation (5 star customer rating)
  • Clustered users into segments using RFM scores
  • Direct impact on customer experience - Loyal customers offered premium services

Intuit inc.

Software Engineer Intern

Jun 2015Jul 2015 · 1 mo · Greater Bengaluru Area

  • Architected scalable REST APIs utilizing the MEAN stack supporting a concurrency of 10K requests with an average response time of 490 ms
  • MongoDB | MongooseJS | ExpressJS | NodeJS | Apache Benchmark | SoapUI

Education

Georgia Institute of Technology

Master of Science - MS — Computer Science (Specialization: Machine Learning)

University of Illinois Urbana-Champaign

Master of Business Administration - MBA

PES University

Bachelor of Engineering - BE — Computer Science and Engineering

National Public School, Rajajinagar

12th

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