Data Sales

Sanika Sameer Moghe Email : adbf6w@r.postjobfree.com

Linkedin: https://www.linkedin.com/in/sanika-moghe/ Mobile : +1-469-***-**** Education

The University of Texas at Dallas Richardson,TX

Masters in Business Analytics; GPA: 3.38 August 2018 - May 2020

University of Pune Pune, India

Bachelor of Engineering in Information Technology August 2014 - June 2018 Skills Summary

Programming: C, C++, Java, SAS, R, Shiny,Python, Stata

Big Data Technologies: Hadoop, Hive, Spark, Pig

Scripting Languages: HTML, PHP, JavaScript, CSS, AngularJS, Ajax

Databases: SQL,PostgreSQL,MongoDB, Cassandra, DynamoDB

Software &Tools: Advanced Excel (VBA, Macros),MS O ce, Google Analytics, SSRS, Tableau, AWS, Power BI

Python Libraries: NumPy, Pandas, SciPy, Matplotlib, Scikit-learn, TensorFlow,Keras Coursework

Data Visualization, Predictive Analytics using SAS, Prescriptive Analytics, Advanced BA with R,Statistics and Data Analysis, Business Analytics in R, Applied Econometrics and Time Series Analysis, Programming for Data Science using Python, Applied Machine Learning, Big Data.

EXPERIENCE

Captsone Project at Child Poverty Action Lab Dallas,Texas January 2020 - Present

Currently working with CPAL to revise the existing Community Resource Index(CRI) to mitigate the root-drivers of child poverty. Using the Census data of 2010,analysis is done on the demographics of the people living in Dallas using Python to determine factors causing child poverty.

Invental Construction Management Group Pune, India Data Analyst Intern June 2016 - August 2017

Implemented Excel and SQL extensively for data cleaning, transformation,processing to convert the data into the format of the in-house standard.Analyzed the historical data of housing prices using Python. Implemented various classi cation and regression models to determine future housing prices as well as the patterns and trends in the various factors a ecting the prices to help achieve the maximum pro t.Plotted the results using trend charts and plots and presented the ndings using reports and dashboards created with Tableau. The project helped increase the pro ts by 9%. Academic Projects

Predictive Analytics Project: Using SAS, performed analysis on the scanner data of sales of Mayonnaise of di erent retail store locations across the US. Integrating data, analysis was performed on the store level panel data and price elasticity was calculated. Multinomial logisitic regression was performed on the panel data for customers and RFM analysis was carried out on the merged dataset of the customer demographic data and the panel data.Insightful recommendations were made that would help the store manager increase sales, target audience for marketing and improve the weaker stores.

Black Friday Sales Data Analysis: The dataset comprises of the sales transaction captured at a retail store during black friday. Using R, performed data cleaning, transformation and Explorartory data analysis, and hypothesis testing on the data to conclude important facts. Implemented machine learning models such as Multiple Linear Regression, Generalized Linear Regression, Random Forest Regression, Support Vector Machine and Extreme Gradient Boosting. Predicted the value of the target variable i.e. Purchase amount using the XGBoost Model.

Applied Machine Learning Project: Developed classi cation models such as KNN classi er, Logistic regression, Linear SVC, Kernelized SVM classi er, Decision Tree using Grid Search to nd the best parameters and use them to conclude that Logistic regression is the best classi er with an accuracy of 97.3% using Python on the Audit Data Dataset to predict the fraudulent rms on the basis of the present and historical risk factors in various sectors.Implemented regression models including KNN regressor, linear regression, Ridge, Lasso, polynomial regression, Linear SVM and Kernelized SVM, to conclude the KNN regressor as the best regressor with an accuracy of 89%. Applied ensemble models such as Bagging,Pasting, Voting Classi ers, Gradient Boosting, ADA boosting to the classi cation and regression models to get better results. Additionally also implemented Deep Learning models. Organizations and Achievements

Scholarship: Recipient of the graduate Dean’s excellence scholarship awarded by the University of Texas at Dallas

Event Coordination O cer: Big Data Club at University of Texas at Dallas.

NGO Bhumi-: Tutored Mathematics to underprivileged children of grade 1 and 2. Publications

Implementing a hybrid of e cient algorithms for mining Top-K utility item-sets. IEEE,2018,India

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