Junling Ren

Phone: 502-***-**** Email: adyykj@r.postjobfree.com Linkedin: /in/junling-ren-415387175/ SUMMARY

Data Scientist with 3+ years of experience in developing machine learning and statistical models to deliver innovative solutions with a strong statistic background, expertise in Anomaly Detection and Risk Assessment in healthcare industry. Excellent communication, presentation skills and great team player. SKILLS

Python (Numpy, Pandas, Scikit-Learn, Matplotlib, Seaborn, SciPy), Machine learning (Linear/logistic regression, Random Forest, XGBoost, Decision tree, Clustering), Statistical/Predictive Modeling, Tableau, SAS, Jupyter, SQL, Tensorflow, Keras, PyTorch, GCP, AWS, Flask, NLTK, Github, Linux/Unix EXPERIENCE

Virginia Commonwealth University Richmond, VA

Research Scientist, Data scientist 06/2019 - Present Oral Disease Risk identifier

Built and tuned an oral microbiome-based predictive model for periodontal disease diagnosis. Collected oral plaque (microbiome) samples in normal and diseased patients, obtained 16s rRNA (bacterial species specific) sequencing data, conducted exploratory data analysis (EDA) and feature engineering; trained and optimized multiple models (Logistic Regression, Random Forest and XGBoost). Five bacterial biomarkers were identified to be significantly associated with periodontal disease and the top- performing predictive model achieved a 90% accuracy, significantly surpassing traditional methods based on doctors' experience. The treatment efficacy improved by 75%. Cancer Recurrence Risk Classifier

Built a classifier to predict the cancer recurrence risk based on the patients' health condition. Collected the historical data; Developed logistic regression and Gradient Boosting model using Python. Performed hyperparameter tuning to achieve a F1 score of 0.88. The cancer recurrence risk prediction accuracy improved by 70% and the patients' survival rate increased by 30%, resulting in approximately $5 million cost saving due to the avoidance of unnecessary treatment. University of louisville Louisville, KY

Postdoctoral Researcher 01/2017 - 06/2019

Exploring whether Oral Bacterial Infection Promotes the Growth of Oral Cancer Analyzed data related to tumor size, weight, RNA-seq and protein level data. Utilized statistical tests like T-test and ANOVA to validate experimental results. Discovered that oral bacterial infection exacerbated oral cancer by significantly increasing PD-L1 expression and published high impacted papers. PROJECTS

Provider Fraud Detector 01/2023 - 07/2023

Developed a Provider Fraud Detector to identify fraudulent providers using binary classification models. Cleaned and processed imbalanced Medicare claims datasets; Applied Matplotlib and Seaborn to visualize data. Optimized multiple classification models (Logistic Regression, Random Forest, and XGBoost). Random Forest classifier (recall: 0.83) successfully identified key fraud indicators and revealed the characteristics of fraudulent providers to generate fraud preventative strategies. Wrapped the optimized model as an API via Flask and deployed it on the Google Cloud Platform (GCP). EDUCATION

Hokkaido University Sapporo, Hokkaido, Japan

Ph. D in life science 04/2012 - 09/2016