Hi,
I am Goutham

Data/Machine Learning Engineer @ Infor

SDE Intern @ Philips

Graduate Student - Information Science

Undergrad Teaching Assistant - University of Pittsburgh

“Jarvis, sometimes you gotta run before you can walk.” - Tony Stark

About

A little about me !

I am Goutham, recent graduate from University of Pittsburgh in Information Science (specializing in BigData). I'm currently working full-time with Infor as a Data/Machine Learning Engineer. I'm always enthusiastic and motivated towards contributing positive business results through effective implementation and amalgamation of software and data.


I'm excited to solve problems as software engineer, possibly leveraging machine learning and actively looking for any open opportunities in organizations that are trying overcome different challenges dedicated to improve people’s lives

Work

Data/Machine Learning Engineer - Infor

SDE Intern - Philips

Information Technology Intern - Automated Health Systems

Associate Software Engineer - UnitedHealth Group(Optum)

Intern - Defence Research and Development Laboratory

Skills

Programming Languages

Databases

Other

Data Science & Cloud


PySpark, Kafka, Scikit-Learn, Pandas, Tensorflow, Keras, Dash, Tableau , Azure, GCP

Recent Projects

Patient Heart Stroke Prediction

Executed machine learning models with target condition of predicting whether a patient is prone to CVD with prime focus on optimal model selecting, dealing with imbalanced data and considering various evaluation metrics, achieved highest accuracy of 79% with Gradient Boosting Algorithms.

YELP User Credibility

Developed a score of credibility for the yelp user’s by using the feature importance matrix generated from models built with XGBoost, LightGBM and SHAP and applying cumulative distribution

Graph based DataWarehouse

Loaded YELP open dataset into three variable databases -MySQL, MongoDB and Neo4j by transforming the data into OLAP format. Extracted analytical and business-critical information from each database using PyConnectors. Compared the efficiency and time of queries in all three databases and displayed them on UI developed with React. Also studied how YELP leverages AWS Redshift and lake house approach for its fully managed data warehouse

Contact

If you are interested to collaborate or would like to discuss anything, please feel free to contact me via an e-mail or any socail media
Email: sru6@pitt.edu