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Hi, I’m Mishika. Welcome to my Github portal.

πŸ‘©β€πŸŽ“ About Me

Looking for a problem solver with a penchant for driving data-driven business decisions? Well, look no further because that is where I come in!

With a robust academic background in the quantitative discipline of Economics and over 3 years of experience in strategy consulting across industry domains, my love for leveraging data to derive actionable business insights led me to "shift gears" and pursue my Master’s in Business Analytics at UCLA Anderson School of Management.

My prior experience of working in the Venture Ecosystem team at Bain & Company enabled me to help Fortune 500 clients with critical insights on the innovation disruption in the startup and venture capital domain using predictive modeling and visualization. What's even more rewarding is the lasting relationships I've built with clients across various sectors including retail, technology, finance, and construction.

I am interested to apply and engage in an internship role that lies at the intersection of business strategy, product development and data science/ analytics. Please feel free to reach out to me at: [email protected]

πŸ“Š Data Science Expertise

  • Languages: Python (NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, Plotly), SQL, R (dplyr, ggplot2)
  • Software/ tools: JupyterLab, Tableau, R-Studio, MS Office Suite, Stata, GIT
  • Analytics: Statistical Modeling, Machine Learning (Supervised learning algorithms), Segmentation Analysis, Time Series Analysis, EDA, Visualization, A/B Testing

Happy to connect on LinkedIn - https://www.linkedin.com/in/mishika12/

Mishika's Projects

classification-tennis_match_winner icon classification-tennis_match_winner

Analyzing past 20 years data of tennis players, understanding and predicting the key factors that impact the winning or losing of tennis player based on their past performance using classification algorithms

regression-walmart_sales_data_analysis icon regression-walmart_sales_data_analysis

Determining the factors affecting Walmart sales and analyzing the impact of markdowns around holidays on the sales; Predicting the sales accurately with regression algorithms like Linear regression, Decision Trees and Random Forest

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