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LifeOf-py/README.md

Hi there 🙌!

I’m Mayank and I’m currently pursuing my Masters in Business Analytics(MSBA) from UMN Carlson School of Management.

I have five years of working experience in Analytics and Data Science. My journey in Analytics started as a Decision Scientist at MuSigma (Bangalore) where I solved interesting problems for our Fortune 500 clients for 3.5 years.

Post that, I was working at Walmart as a Senior Data Analyst for 1.5 years where my role revolved around recommending in-demand items to sellers to onboard on walmart.com, using different customer demand signals.

Fun Fact - In case you purchased an item from Walmart in the last couple of years, there is a high chance that item was recommended by me!

What I bring to the table?

Speed, Spearheading & Strategic Thinking

Let's Connect!

📧: sing1329@umn.edu

🤝: LinkedIn

My Motivation?

🏎️: Porsche 911 GT3 RS

🥷: Always chasing 11.2 km/s!

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  1. Cost-Sensitive-Spam-Classification Cost-Sensitive-Spam-Classification Public

    Spam detection with cost-sensitive learning using custom loss (10× FP, 1× FN). Includes LightGBM modeling, nested CV, and business-focused evaluation with ROC, PR, and lift curves.

    Jupyter Notebook

  2. Customer-Spending-Prediction-with-XGBoost Customer-Spending-Prediction-with-XGBoost Public

    Regression modeling to predict customer purchase amount using XGBoost, LightGBM, and Neural Networks. Includes nested cross-validation, hyperparameter tuning, and RMSE evaluation.

    Jupyter Notebook

  3. Interpretable-Machine-Learning Interpretable-Machine-Learning Public

    An approach to deep dive into black-box models

    Jupyter Notebook

  4. Marketing-Analytics Marketing-Analytics Public

    Predicting which people would be likely to convert from free users to premium subscribers in the next 6 month period, if they are targeted by our promotional campaign.

    Jupyter Notebook 1