Mar 2022 – Dec 2023 · 1 yr 9 mos · Bengaluru, Karnataka, India

• Built and scaled a mentorship platform for IIT-JEE aspirants.
• Designed the mentorship model and scaled to 100+ IITian mentors.
• Led product, growth, and sales strategy; scaled YouTube to 20K+ subscribers.

May 2021 – Dec 2023 · 2 yrs 7 mos · Bangalore Urban, Karnataka, India

• Founded a personalized learning platform for competitive exam preparation.
• Achieved 30K+ app downloads and $100K+ ARR.
• Built and led a team of 18 full-time employees + 25 interns.
• Drove organic growth to 50K+ social followers.
• Featured by Inc42, TiE Global, Huddle, and won Unicorn Pitches India.

Jun 2019 – Dec 2021 · 2 yrs 6 mos · Bengaluru Area, India

• Worked on LinkedIn Learning Search & Recommendations.
• Shipped personalization improvements resulting in $1.5M+ monthly revenue uplift.
• Improved ranking systems using recency, popularity, and engagement signals.
• PM-adjacent work on LinkedIn Events flows and spam reduction.

Dec 2018 – Jun 2019 · 6 mos

• Applied machine learning techniques to model risk management to assess and mitigate financial and trading risks.
• Collaborated with cross-functional teams to identify high-risk areas and strengthen risk evaluation frameworks.
• Built and evaluated multiple ML-based risk models to analyze trade-level and portfolio-level risk.
• Translated complex model outputs into actionable risk insights to support informed decision-making.

Jun 2018 – Dec 2018 · 6 mos

May 2017 – Jul 2017 · 2 mos · Bangalore, india

Dec 2015 – Jan 2016 · 1 mo · Mumbai Area, India

• PROJECT 1
• Built a best in class recommender engine to provide users recommendation based on their stated preference
• Built a movie recommender system that corrects recommending movies to the users. The complete code was built in Python and R.
• The solution is similarity between different viewers using cosine similarity, identifies top recommended by ranking movies using collaborative filtering algorithm, extract images of movies from websites using web scraping and finally built a simple user interface
• Built a user interface using KNIME & UI elements that integrated within Centralised Analytics environment (CAE) of Fractal Analytics
• PROJECT 2
• Studied Supervised learning algorithms built in Python/R and provided an analysis of how and when to use specific algorithm
• Analyzed supervised learning algorithms-neural networks, k-nearest neighbours, SVMs, logistic regression, decision tree and provided a summary of which algorithm to pick based on different business scenario to arrive at a more accurate and efficient solution
• Conducted detailed study on bias-variance trade-off of advanced machine learning algorithms like bagging(random forest), boosting(Gradient boosting machine and Adaboost). Tested the results through implementation on various Kaggle datasets like Rossmann Sales Forecasting and Higgs Boson challenge.

Jun 2015 – Jul 2015 · 1 mo · Bengaluru Area, India

• Modelling and Validation of Probability of Default (PD) using Regression Analysis (Logistic Regression) and Big Data Technologies
• Tools used : R, Excel, MySQL, Shiny - R (UI development)

Feb 2015 – Mar 2016 · 1 yr 1 mo

• Ensure the welfare of all the undergraduate students of the institute by
• providing them emotional, academic and financial assistance.
• Worked in team of 12 and proposed various ways for better interaction
• of students and faculty members.

May 2014 – Jul 2014 · 2 mos · IIT Kanpur

• Completed courses on advanced C++, Web Programming and Algorithms.