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Sagar Jounkani

Data Scientist @ GE Healthcare

Professional Overview

Data scientist at GE Healthcare with over 4 years of experience in analytics in the 'US healthcare' and 'E-commerce' domains. Enjoys working on large scale data to develop insights which drive business action. Core skills include -

  • Proficiency in Python, R, SQL, SAS and Excel
  • Exploratory data analysis and machine learning 
  • Good communication skills, strong business acumen, high degree of initiative and a continuous learning approach

Work Experience

Mar 2018Present

GE Healthcare

Data Scientist
  • Advanced troubleshooting - Developed predictive models to serve recommendations to service engineers for troubleshooting service requests. The project involved designing labels using unsupervised learning, textual data processing, modelling the solution while taking into account high modality label space with class imbalance. The project also involved interacting with end business users and designing a system which has a feedback loop to facilitate continuous learning. 
May 2016Mar 2018


Software Engineer - Data Science
  • Sentient - The project involves using NLP models on textual and speech data incoming at the customer care center and surfacing customer pain points, anomalous service breakdowns and pre-order questions which can lead to 'escalations'. The use cases are aimed at preventing churn and improving customer redressal.
  • Churn driver analysis - Worked on developing a causal model for churn scores. This model helped the revenue and marketing team identify major drivers for churn leading to the implementation of a more targeted customer retention strategy.
  • Return item quality predictor model - The target feature recognizes an abused return item and helps Myntra decide whether to do 'Inward Quality Check (IQC)' or not - hence, saving on cost and manpower and reducing average return refund time by half. Contributed by engineering features and developing tool for evaluating model performance across service and revenue parameters
  • Pained customer redressal framework - Quantified the impact on customer transaction frequency due to various service/experience short-falls. On the basis of which designed a framework for redressing pained customers and improve customer retention.
    • Developed a near real-time unit-level pendency report across  forward and return supply chain nodes to provide insight into service breakdowns and improve resolution time.
    • Designed models to ascertain the impact of vendor de-listing on metrics like overall delivery time, returns percentage and Myntra-initiated-cancellations
May 2014May 2016

ZS Associates

Business Associate
  • Designed, managed and made functional improvements to sales force effectiveness models pertaining to incentive compensation, goals setting and customer targeting



B.Tech - ECE - VIT University

  Projects -
- Sensible Electronic Blind Cane
- Low-cost Gesture Aided Computer Control System for the disabled
- Hand Gesture Recognition application using Image Processing


ICSE (91.2%)  and ISC (89%)

St. Francis' College