Rushabh Shah

Dallas, TX 682-***-**** adb25z@r.postjobfree.com www.linkedin.com/in/rushrshah

EDUCATION:

The University of Texas at Dallas, Dallas, TX expected December 2020 Master of Science in Business Analytics specialization in Data Science GPA 3.84/4 Nirma University, Gujarat, India May 2017

Bachelor of Technology in Electrical Engineering

TECHNICAL AND LANGUAGE SKILLS:

Programming Competencies: Java · Python (NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras) · R · SAS Database and Big Data: MySQL · NoSQL · PL/SQL · Hadoop · HDFS · Spark · Hive · Sqoop · Impala · Spark · MongoDB Data Visualization: Tableau · PowerBI · ggplot (R) Cloud Technology: AWS (Route53, EC2, S3, CloudFront, RDS, RedShift, DynamoDB, EMR, VPC) · Google Analytics EXPERIENCE:

The University of Texas at Dallas – Dallas, Texas, United States January 2020 – Present Graduate Teaching Assistant

• Statistics and Data Analytics OPRE 6301 and Quantitative Business Analysis BUAN 6398 I-link Infosoft Solutions Pvt Ltd. – Ahmedabad, Gujarat, India July 2018 – February 2019 Software Developer II

• Implemented digital marketing strategies to engage customers to company website augmenting view rate from 19% to 37%

• Developed python and SQL code scripts for automating 20 everyday tasks slashing 14 rework man hours every week

• Computed descriptive statistics of emails delivered, spammed, reported, bounced back with response received from recipients

• Deciphered data to build predictive models using regression techniques to estimate customer behavior and classify emails

• Used time-series forecasting to find trends & seasonality in customers clickstream by creating dashboards & reports on Tableau

• Boosted email batch size by 20% to 1.21 million by using parallel sending servers & diversifying receiving domains Infosys Pvt Ltd – Pune, Maharashtra, India December 2017– July 2018 Machine Learning Engineer – Reliance Retail Market (eCommerce)

• Incorporated new online payment interface API’s for PayPal and Google pay that increased new user adoption rates by 15%

• Designed and built statistical analysis models to help increase online sales by 7% and lower cart-abandonment rate by 23%

• Implemented clustering algorithms to leverage marketing strategies for targeted consumer-centric advertisements

• Retrieved data by web scraping customers review & ratings on products to performed sampling techniques to derive insights Infosys Pvt Ltd – Pune, Maharashtra, India May 2017 – December 2017 Software Developer - IRCTC (Indian Railways Catering and Tourism Corporation)

• Developed, tested & debugged code using object-oriented programming principles abiding to government constraints

• Increased code coverage of customer portal by 43%; enhanced code usability and efficiency to ensure smoother workflow

• Improved data mining process by displaying trains 17% faster & decreased average ticket booking time at peak web traffic

• Extracted, imported & manipulated large volume of data from varied sources whilst ensuring consistency across MVC layers Doordarshan Kendra – Ahmedabad, Gujarat, India August 2016 – January 2017 Data Science Intern Co-op

• Worked on channel level analysis to determine geographical positioning of viewers; deduced total audience share of 23.90 %

• Mapped out seasonality in reach, viewership & audience migration to find spikes before and during Cricket ODI Series

• Segregated urban segment viewership share (59.2%) & rural share (40.70%) to allocate new installation of TV towers PROJECTS:

Fashion MNIST – Kaggle Techniques – Convolution Neural Networks Classified images to 10 categories of clothing by implementing deep learning with Keras and achieved a 93% acute prediction rate. Appliance Energy Prediction – Kaggle Techniques – Linear Regression, Gradient descent, Logistic Regression Implemented both regression and gradient descent algorithm from scratch and optimized cost function for different learning rates. California Housing Prices – Kaggle Techniques – Linear Regression, One hot encoding Predicted the median housing price value for each district by optimized feature selection and creating mathematical linear models. Using News to Predict Stock Movements - Kaggle RANKED 4th Techniques - XGBoost, CatBoost Used news & market data to anticipate performance of a stock by apt selection of characteristic from sea of available attributes. Home Credit Default Risk – Kaggle Programming- Advanced MS Excel, MySQL Cleaned data to load in staging tables; normalized data to 3NF; plotted ER diagram; designed DB schema; ran validation queries Playoff Projection of NBA teams – Kaggle

Developed model to forecast if a team will make the playoffs or not; achieved 92% accuracy comparing them to the actual result Deep Learning, Machine Learning, Graph AI (GCN, GNN), Topological Data Analysis, Natural Language Processing, Generative Adversarial Networks, Adversarial Learning, Human Computer Interaction, Behavioral Science, Computational Cognitive Science, Knowledge Processing