Jul 2025 – Nov 2025 · 4 mos · Bengaluru, Karnataka, India · On-site

Oct 2023 – Jun 2025 · 1 yr 8 mos · Bengaluru, Karnataka, India · On-site

Jul 2022 – Sep 2023 · 1 yr 2 mos · Mumbai, Maharashtra, India

Aug 2021 – Jun 2022 · 10 mos · Mumbai, Maharashtra, India

Sep 2018 – May 2020 · 1 yr 8 mos · Mumbai

• As a Senior Business Analyst in InterMiles' Advanced Analytics team, I work closely with cross-functional teams to develop analytical frameworks and implement solutions that aim to bring rewarding value to InterMiles' 10 million members. I leverage customer data and use statistical and Machine Learning techniques to get insights into customer behaviour, which is used to enhance the firm's profitability at an overall portfolio level.
• I was recently involved in developing the pricing strategy for JetPrivilege’s new Select Flights platform, which is a critical project for the company. This strategy would allow JetPrivilege members to book flights on any airline globally. I work closely with the Airline Partnership team to determine the optimal price that members should pay for buying airline tickets on this platform.
• I was also responsible for building the Hotels Look-Alike model for JetPrivilege's new Hotels platform. A Logistic Regression model was built to identify members who would be most likely to engage in a Hotels transaction. The insights were used by Marketing to send personalised campaigns to members, driving JetPrivilege's customer acquisition target.
• Moreover, I worked on an ML based Customer Lifetime Value model, which implemented an ensemble of Logistic Regression and XGBoost to predict the worth of business a member would engage in with JetPrivilege. ML based Lifetime Value prediction models are very new to the Loyalty industry, with scanty literature, which makes this a unique project.

Jul 2016 – Aug 2018 · 2 yrs 1 mo · Mumbai Area, India

• As a management consultant with PwC’s advisory practice, I primarily work in the Consumer Markets and Industrial Products sector, and deliver bespoke client solutions leveraging data driven analytics and statistical modeling.
• I was responsible for developing the analytics layer in PwC's proprietary Predictive Maintenance platform, a tool that helps airline clients realize cost savings by predicting delays and cancellations ahead of a scheduled departure. We use airplane sensor data to model failure probabilities, using statistical techniques like Rare Event Logistic models and Machine Learning algorithms like Random Forest, and help the airline maintenance crew to prioritize maintenance and repair jobs. The Predictive Maintenance solution was deployed for a Fortune-500 cargo airline company.
• Other engagements I have worked on includes a market benchmarking exercise to help a US Private Equity client analyze the benefits of acquiring a firm that specializes in manufacturing of brewery equipment, and an Account Segmentation and Distribution engagement for a Fortune 500 brewing company.
• I have also worked in the Innovations sector, where PwC leveraged cloud based AI capabilities to develop Image Analytics models, to detect diabetes in patients based on images of the patient's’ eyes.

May 2015 – Jul 2015 · 2 mos · Mumbai Area, India

• Worked with the Global Markets Commodities Research desk to develop a model to predict WTI crude oil prices in the short run, using market fundamentals and industry knowledge.