Headline

PhonePe | EXL | Axis Bank | IIT Delhi

About

Machine learning and analytics professional with strong experience in credit risk modeling, experimentation, and building data-driven decision systems at scale. Currently working at PhonePe, driving end-to-end analytics for lending products, improving conversion through A/B testing, and developing real-time eligibility and risk models that impact millions of merchants. Hands-on experience in solving large-scale financial problems, including identifying high-risk customers across massive datasets and building predictive models to reduce delinquency. Comfortable working across the full lifecycle, from feature engineering and model development to pipeline automation and production deployment. Proficient in Python, SQL, PySpark, and modern ML frameworks, with a solid grasp of statistical methods and experimentation. Backed by a strong academic foundation from IIT Delhi and published research in deep learning and medical imaging. Focused on using data to drive meaningful business impact while continuously learning and evolving in the field.

Location

Bengaluru

AI stack

codex

cursor

Work experience

Analyst at PhonePe, Apr 2025 - Present · 1 yr 5 mos, Bengaluru, Karnataka, India, Credit Risk Management

Consultant at EXL, Oct 2023 - Apr 2025 · 1 yr 7 mos, Gurugram, Haryana, India, - High Credit Risk Customer Identification - Marketing Campaign Budget Optimization

Data Scientist [Business Intelligence Unit] at Axis Bank, Jun 2022 - Jul 2022 · 2 mos, Bengaluru, Karnataka, India, - Performed data cleaning, preprocessing after fetching 50+ features for 3.30 crores live customer base in SAS. - Conducted feature selection using Pearson's Correlation and Random Forest Feature Importance on Pyspark; created data pipeline. - Implemented Weighted Logistic Regression on selected features for our class imbalanced data, achieving 0.76 AUC ROC on test data. - Represented customers in decile, based on their propensity score whether they would invest in TD in the following 3 months.

Summer Research Intern at AIIMS (All India Institute of Medical Sciences, New Delhi), May 2021 - Jul 2021 · 3 mos, New Delhi, Delhi, India, - Implemented several CNN based architectures like UNet, Double UNet, etc for left ventricle segmentation on Cardiac MRI data. - Performed preprocessing to read DICOM files & augmentation techniques to increase dataset, achieved best dice score of 90%. - Built an interactive workspace for doctors to manually contour the prediction and calculate the ejection fraction of the left ventricle.

Research Intern at University of Notre Dame, May 2020 - Jun 2020 · 2 mos, Indiana, United States

Education

B.Tech & M.Tech (Dual Degree), Chemical Engineering, Indian Institute of Technology, Delhi

Minor Degree, Business Management, Department of Management Studies, IIT Delhi

Public links

github: https://github.com/rik030