Data Scientist Intern Resume
Burlington, NC
TECHNICAL SKILLS:
R: 3 years of experience in statistical programming, Data Visualization (ggplot2/shiny), Version control
Python: 2 years of experience in machine learning (sklearn/tensorflow), Spark (pySpark)
SAS: Working experience in PROC SQL, macro programming, etc.
Statistical modeling: A/B testing, GLMs, Predictive Models, Hypothesis Testing, Experiment Design, Hierarchical Models
Machine Learning: Supervised learning (Regressions, SVM, Tree models, Na ve Bayes, GLMs, etc.), Unsupervised learning (Clustering, PCA, etc.), Deep Learning, NLP
Big Data: Spark, Hadoop, HDFS, Hive
Coding: Scala, SQL, Java, HTML, CSS, NodeJS, XML, JSON, JavaScript
PROFESSIONAL EXPERIENCE:
Confidential, Burlington, NC
Data Scientist Intern
Responsibilities:
- Researched, acquired data, and built a classification model for the lab testing insurance claims denials. Achieved 89% prediction accuracy of the declined lab testing insurance claims using gradient boosting trees.
- Automated the ticket request for selecting patients with targeted mutations
- Built a desktop app for connecting the database and monitoring the ticket processing status using Python PYQT5 and py2exe packages
- Implemented TF - IDF feature extraction algorithm to identify patients with targeted mutations
Confidential
Data Analyst Intern
Responsibilities:
- Established optimal customer selection platform through logistic regression model in SASAchieved 3.3 lift measure at 20% of the testing population by feature engineering and variable selection
- Reduced the model performance monitoring procedure to seconds by automating data extraction and analysis steps
- Developed the guidelines and best practices report for selecting customers based on the predictive model analysis
Confidential, Greensboro, NC
Actuarial Summer Analyst
Responsibilities:
- Conducted the loss reserve study using new segmentation method•Wrote a bootstrap program in SAS to generate a synthetic portfolio for catastrophic model tests
- Converted the VONB Excel model to SAS model for better scalability
- Improved the logic and readability of the reserve model in Excel