YASHWARDHAN KAUL

Chicago, IL ***** 312-***-****

adg5mt@r.postjobfree.com www.linkedin.com/in/yashwardhan-kaul

Professional Summary

Motivated and results-driven Analyst with proven track record in data analytics and data governance. Proven ability to identify business needs and develop valuable solutions to drive accuracy and process efficiency. Drives business effectiveness through making recommendations based on data findings.

Skills

Technologies: Github, Jira, Hadoop, Spark, Tableau, SAS, Keras, Pytorch, Tensorflow.

Enterprise application integration

Natural Language Processing

Cloud - Google Cloud Platform, AWS, Azure

Data Governance

Programming Languages - Python, R, AngularJS, SQL

Data Quality Assurance Processes

Machine Learning

Database Management Expertise

Work History

Data Analyst (Graduate Assistant) Jun 2019 - Current

UIC Academic Affairs – College of Business Administration Chicago, IL

Updated organizational and data retrieval subsystems to improve and streamline data collection.

Recommended data standardization and usage for protection of data integrity.

Set up blind assessments for 500+ term papers and managed assessment teams consisting of faculty for enhanced experimental bias reduction.

Data Analyst Jun 2020 - Aug 2020

SE2 LLC Topeka, KS

Coordinated statistical data analysis, design, and information flow to derive insights for solutions team.

Evaluated Call Center and policy data with more than 30 million rows for trends to understand competitive environments and assess current strategies.

Created robust Data Governance strategy and roadmap consisting of scope, initiation, policies, principles and deployment strategies.

Software Development Engineer May 2016 - Dec 2016

Keelvar Systems Pvt. Ltd. Cork, Munster, Ireland

Built and maintained robustness of various parts of their online procurement web application which uses machine learning techniques to provide optimized sourcing to companies such as Coca-Cola and Siemens.

Provided support to Senior Business Analyst and gained experience interacting with customers.

Monitored ongoing operation of assigned programs and responded to problems by diagnosing and correcting logic and coding errors.

Implemented automated testing on 50+ views using Protractor for streamlined testing and increasing development speed.

Education

Master of Science: Business Analytics Expected in Dec 2020

University of Illinois At Chicago Chicago, IL

Coursework in Advanced prediction modeling, big data analytics, advance database management, data mining, statistics for business and advanced text analytics

Current GPA 3.66/4

Bachelor of Engineering: Electronics and Computers Engineering May 2018

University of Limerick Limerick, Ireland

Coursework in Artificial Intelligence, Machine Vision, Computer Architecture, Spatial Robotics and Software Development

Received 50% Scholarship

Graduated with 3.4/4 GPA

Certifications

Data Engineering, Big Data and Machine learning on Google Cloud Platform Specialization

Projects

Multi-Class Multi-Task Classification Model to predict age, gender and race (May 20)

Successfully implemented a multi-task cascaded CNN using transfer learning on the UTKFace dataset.

Deployed VGGFace architecture and compared results of transfer learning model vs. baseline CNN model. Best model accuracy ~ 85%

Loan Default Prediction – Lending Club (Nov 19)

Predicted loan default by building model on 35 most relevant variables out of 495.

Performed data exploration, data reduction, variable selection with random forests, data imputation with KNN, best prediction accuracy from GBM model (85%).

Calculated profit/loss curve using confidence intervals.

Fundraising for Paralyzed Veterans Association of America. (Oct 19)

Built entire pipeline for prediction of donors with a random forest model (90% accuracy on validation set) and prediction of donation amount with LASSO regression model (84% accuracy on validation set).

Measured donation curves with different model and different hyper-parameters to find the best.

Models used – RIDGE, LASSO regression (PCA used), Random forests, SVM, KNN, GBM.

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