• Analyzed therapy effects on outcome measures using SAS and R, interpreting p-values to informtreatment effectiveness• Created a PowerBI dashboard to present monthly and annual KPIs to leadership and board members• Generated informative visuals using matplotlib and seaborn to highlight performance gaps across eleven partner organizations• Managed back-end data using stored procedures and SQL queries

• Developed prediction and classification models (logistic regression, random forest, neural network) using scikit-learn and tensorflow, decreasing likelihood for customers to escalate to agents by 14%• Implemented an ETL process for digital customer feedback data, allowing a smoother transition from raw data to actionable insights• Identified actionable items to address top customer concerns by parsing open-ended feedback responses• Revamped the company’s data portal for ease of use, improving company KPIs by an average of 5%

• Regularly monitored and reported on data quality, detecting possible anomalies in data collection• Automated the data extraction process for psychophysiological and behavioral data using nested Excelfunctions and VBA macros, reducing a month-long process into a couple hours• Analyzed the causal relations between mental health and biological markers using linear regression andmixed effects models in SPSS

• Handled data collection and management for multiple grant-funded projects• Provided progress reports for partner sites and summarized data collection using pivot tables,graphs, and charts on Excel• Implemented quality checks and data quality assurance protocols to ensure data integrity• Provided weekly consulting for research teams on extracting and managing datasets