Data Analyst

RASIKA PAWAR

Dallas, TX ***** I . _ 479-***-**** ***************@*****.*** Rasika Pawar

EDUCATION:

The University of Texas at Dallas, TX, USA Aug 2019-May 2021 Master of Science in Information Technology and Management GPA: 4.0/4.0 Pune Institute of Computer Technology, India Jun 2013 - Jun 2017 Bachelor of Engineering in Information Technology GPA: 3.33/4.0 TECHNICAL SKILLS:

Programming Languages: Python, R, SQL Cloud: AWS, Azure Databases: MySQL, SAP HANA, MS SQL, PL/SQL, PostgreSQL, Mongo DB Data Science: NumPy, Pandas, Scikit-Learn, Matplotlib, TensorFlow, Keras, Deep Learning BI Tools: Tableau, Power BI, Google Analytics, Matplotlib Other: Alteryx, Excel, Microsoft Office, ETL, Data Modeling Relevant Coursework: Business Analytics (BA) with R, Statistics & Data Analysis, Business Data Warehousing, Big Data, Web Analytics, Programming for Data Science, Spreadsheet Modeling, Cloud Computing, Advanced BA with R PROFESSIONAL EXPERIENCE:

Behavioral Health Group (BHG) Dallas, TX, USA

Data Analyst Intern Jul 2020 - Nov 2020

• Processed, cleaned and extracted data from BHG’s existing database for data mining, data modeling and analysis.

• Worked on Big Data and developed Alteryx workflows, SQL scripts and Python scripts to validate data and maintained data integrity across 70 different locations.

• Utilized Advanced SQL – CTE’s, window functions, joins to populate data of over 7 million rows and performed ETL on data as per key business requirements.

• Designed and developed interactive Power BI dashboards for end-to-end reporting with multiple KPIs to democratize financial information to the Executive Management that aided data-driven decisions.

• Technologies: MS SQL, Power BI, Alteryx, Excel, Python. Accenture Pune, MH, India

Data Analyst Oct 2017- Mar 2019

Credit Risk Modelling

• Built statistical models to identify overdrawn credit card customers, delinquent accounts, and transaction patterns

• Strategized the bank’s lending decisions by developing Credit Risk Models to predict defaulting customers across payment cycles and developed a Shadow Rating model (statistical model combining PD, LGD, EAD) to rank borrowers on a given set of parameters.

• Technologies: Python, MS SQL, Power BI, Excel

Target Marketing

• Reduced market spends by 11% by optimizing credit card marketing initiatives using Propensity Models and Segmentation.

• Developed banking-product recommender by conceptualizing the Share of Wallet metric through analysis of customer spending’s which lead to an 8% increase in customer engagement.

• Designed high-performance dashboards to visualize performance metrics of Wells Fargo credit cards against competing brands in the market.

• Technologies: Python, MS SQL, Tableau, Power BI, Advanced Excel PROJECTS:

Auto Tagging of Music Using Neural Networks Jun 2016-Mar 2017

• Implemented two models based on concepts of Convolutional Neural networks (CNN) & Convolutional Recurrent Neural networks (CRNN) and trained them to classify audios based on different hierarchical features.

• Validated the model and predicted multilevel tags such as genre, instruments, and emotions for audio tracks.

• Identified the best model based on predictions and accuracy obtained and then, improved the overall performance

• Technologies: Python, Machine learning, Neural Network, Keras, TensorFlow, Deep Learning Predicting Titanic Survival with Machine Learning in R Dec 2015-Mar 2016

• Implemented Logistic Regression Algorithm, Support Vector Machine, Feature Engineering to generate predictions on who would survive the famous 1912 sinking of the RMS Titanic passenger liner.

• The various attributes about the passenger such as their class (1st, 2nd, 3rd), sex, age, name, fellow travelers, and more were considered.

• Technologies: R, Logistic Regression Algorithm, Support Vector Machine, Feature Engineering

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