🎓 Graduate Student in Business Analytics at the Carlson School of Management, University of Minnesota – Twin Cities.
💼 Former Data Analyst at Capgemini with experience in Python, SQL and SAP HANA.
🔍 Passionate about leveraging data to drive business insights and decision-making.
I'm a data enthusiast with a strong foundation in analytics and a keen interest in machine learning and natural language processing. My academic and professional experiences have equipped me with the skills to tackle complex data challenges and deliver actionable solutions.
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Programming & Analytics
Python, R, SQL, Excel, Tableau, Power BI, SAP ABAP on HANA, Git
Exploratory Data Analysis (EDA), Data Visualization -
Big Data & Cloud Platforms
Databricks, Apache Spark (Structured Streaming, Spark MLlib), Hadoop, Kafka
Snowflake, BigQuery, AWS SageMaker -
Machine Learning & Predictive Analytics
Supervised & Unsupervised Learning, XGBoost, LightGBM, CatBoost
PyTorch, TensorFlow, NLP, DBSCAN, Bayesian Optimization
Predictive Modeling, Time Series Forecasting -
Experimentation & Causal Analysis
A/B Testing, Multivariate Testing, Causal Inference, Experimental Design
Statistical Modeling, Observational Analysis
Here are some of the projects I've worked on:
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Cats vs. Dogs Image Classification using ResNet-50: Image classification of cats vs. dogs using transfer learning with ResNet-50. Achieved ~98% accuracy using Keras and TensorFlow on the Kaggle Dogs vs. Cats dataset.
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Real-Time Movie Recommendation System: Developed a PySpark-based real-time recommendation engine as part of a semester-long project to personalize movie suggestions.
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Predictive Models: Built five predictive models covering classification and regression tasks like cancer detection, car value estimation, and customer spending. Includes cost-sensitive modeling techniques.
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Causal ROI Analysis of Sponsored Search Ads at Bazaar.com: Assessed ROI of sponsored search using Difference-in-Differences regression. Corrected pre-post biases to isolate true ad impact.
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Measuring Display Ad Impact – A Causal Analysis of Star Digital’s Campaign: Evaluated a display ad campaign with randomized trial data. Used causal inference to quantify the ad's effect on user behavior.
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Causal Inference with Experimental Data: Used R to analyze experimental impacts of Reddit Gold on engagement and a tutoring program on test scores. Applied statistical testing and DiD regression.
Feel free to reach out for collaboration or just to say hi! 📧 Email: kotia006@umn.edu, kotian484@gmail.com
You can view or download my resume here.
