Ryan D. Abnavi

Data Scientist & Machine Learning Engineer Available: May 2021

adjggp@r.postjobfree.com linkedin.com/RyanAbnavi githab.com/RyanAbnavi Google Scholar 216-***-**** Experience

Data Scientist Intern May 2020 – Aug 2020

Apex Analytix Greensboro, NC

• Performed data migration and storage using sqlalchemy in SQL server and Snowflake

• Found similar invoices from a large dataset (1 TB) and created a new dataset

• Built & optimized ML models to predict duplicate payments in a production environment

• Improved duplicate payment detection model performance by at least 15%

• Built and trained ML models for extracting contact information from email signature Data Scientist Aug 2020 – Jan 2021

Cleveland Clinic Remote

• Collected COVID related texts from Twitter, governmental & scientific sources using web scraping and APIs

• Applied NLP techniques to preprocess unstructured text data

• Classified documents using unsupervised topic models (NMF, LDA)

• Built and optimized a semi-supervised model (CorEx) using anchor words from unsupervised models

• Interpreted results to show the difference between governmental & scientific community’s concerns about COVID Teacher & Research Assistant Jan 2017 – May 2021

Cleveland State University Cleveland, OH

• Designed and implemented experiments, statistical analysis of data, visualization and interpretation

• Developed models for predicting chlorine level and pathogen contamination in fresh produce washing process

• Optimized hyper-parameters using Levenberg–Marquardt algorithm for ODEs

• TA Courses: Introduction to Programming (Python), Introduction to Algorithms Projects

Fraud Detection Imbalanced data, Binary classification Sep – Oct 2019

• Predicted fraud transactions using XGBClassifier and Hyperopt with AUC of 0.9245. Text Toxicity Detection NLP, Text classification Jun – Jul 2019

• Detected toxic comments using CNN with simple LSTM with AUC of 0.9342 House Price Prediction Tabular data, Regression Jan – Apr 2019

• Lowered the RMSLE to 0.1143 using weighted bagging of XGBRegressor, LGBMRegressor and a stacked model comprised of ElasticNet, KernelRidge and GradientBoostingRegressor (Top 1% in Kaggle competition) Education

Ph.D. in Chemical Engineering minor: Statistics Jan 2017 – May 2021 Cleveland State University Cleveland, OH

• Courses: Discrete data analysis - Design & analysis of experiments MicroMasters in Computer Science May 2019 – Jul 2020 MITx edx.com

• Courses: Machine Learning - Design & Analysis of Algorithms - Artificial Intelligence Certificate in Data Science Aug 2018 – Apr 2019

Case Western Reserve University Cleveland, OH

• Topics: Deep Learning, Neural Networks, Databases, Front-End Technologies, Big Data Bachelor & Master in Chemical Engineering Sep 2005 – Aug 2012 Shiraz University & Sharif University of Technology Shiraz & Tehran, Iran Technical Skills

Technical: Machine Learning, Neural Networks, NLP, Image Classification & Object Detection, Data Analysis, Relational Databases, Data Warehouse, Data Visualization, Social Meda Mining, Web Scraping Programming: Python (Pandas, NumPy, Scikit-Learn, Keras, TensorFlow, PyTorch, NLTK, Regex, sqlalchemy), SQL

(MySQL Snowflake, Postgres), MATLAB, JavaScript, HTML/CSS, R, Git, AWS

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