Ashish Mohanan

Experience

• 

  Mu Sigma Inc.

  Jul 2016 - Jun 2019

  Worked for a Fortune 100 automobile manufacturer and played a role in three different projects that include:Health of the business: • Was a part of the team that developed a PowerBI report to evaluate health of the business by assessing various KPIs at different levels• Played a vital role in designing the Oracle SQL back-end data used to populate the dashboard Customer Targeting: Optimized lead targeting by curating a scored lead list with an accuracy of 85% to maximize revenue and footfall at dealershipsSales & Operations Excellence:• Built a Time Series model for forecasting demand of aftermarket parts with an accuracy of 83% • Developed an MS Access tool to review forecasts and formulated a methodology to identify potential problem parts leveraging forecasts and various supply metrics Show less Worked with one of the largest P&C insurance company in the US. Was a part of three teams: Lead Management and Modeling: • Built propensity models with accuracy in the ballpark of ~70% for different lead behaviors to improve targeting efficiency • Identified potential savings of ~1M by pruning underperforming TV networks displaying Ads utilizing k-means clustering• Reduced lead acquisition costs by 15% by identifying potential online quoters using AdaBoost classification modelMarket Research: • Identified key areas for improvement by sentiment analysis of survey responses and social media comments• Provided insights on domains for improvement across geographical regions by designing and performing hypothesis tests across business functional areasClaims: Designed a text mining framework to capture critical claims to expedite claims evaluation process and boosted accuracy by 21 percentage points Show less

  • Decision Scientist

    Mar 2018 - Jun 2019

  • Trainee Decision Scientist

    Jul 2016 - Feb 2018
• 

  Carnegie Mellon University

  Jun 2020 - Aug 2020

  Graduate Research Assistant

  • Assessed the difference in baseline characteristics between readmitted and non-readmitted patient groups• Predicted patient readmission in the short (<30 days) and long (<1 year) terms using classification models like Random Forest, SVM, AdaBoost, and XGBoost• Identified key predictors of readmission post TAVR

• 

  Carnegie Mellon University - Heinz College of Information Systems and Public Policy

  Aug 2020 - Oct 2020

  Graduate Teaching Assistant

  Graduate Teaching Assistant for Intermediate Database Management (95-813)

• 

  Pennsylvania Department of Labor & Industry

  Aug 2020 - Dec 2020

  Student Consultant
• 

  ZS

  Feb 2021 - Feb 2024

  • Decision Analytics Consultant

    Jan 2023 - Feb 2024

  • Decision Analytics Associate Consultant

    Feb 2021 - Jan 2023
• 

  Genentech

  Feb 2024 - now

  Data Analytics Manager