Experience

National Funding

• United States
• Financial Services
• 100 - 200 Employee

• Data Scientist

  • Apr 2023 - Present



Near

• United States
• Technology, Information and Media
• 200 - 300 Employee

• Data Scientist

  • Apr 2021 - Feb 2023

  - Developed methods like Bayesian inference to estimate hourly visitation to point of interests especially to locations with little information- Used numerous machine learning methods and statistical analysis to help clean fraudulent mobile location data from our ecosystem- Improved previous algorithm that predicted the number of people seen in a location using mobile devices by controlling the impact of device data fluctuations, adding in additional features, and improving the model to give better results using PySpark and SQL Show less

• Data Analyst

  • Jul 2019 - Apr 2021

  - Presented meaningful insights and recommendations to clients using mobile location data to answer their questions- Wrote Python scripts to create customized analyses on large datasets for numerous clients or R&D purposes- Managed several internal R&D projects to improve current products and developed new ones like determining the best combination of parameters to screen out potential outliers from our data ecosystem- Visualized findings through numerous data visualization softwares like Tableau, Carto, and R and packaged those findings using Microsoft Powerpoint or Tableau dashboard for clients and other departments Show less



National Center for Ecological Analysis and Synthesis (NCEAS)

• United States
• Research Services
• 1 - 100 Employee

• Scientific Computing Intern

  • Nov 2018 - Jun 2019

  - Wrangled research data into formats more appropriate for analysis using R - Created visualizations using ggplot and used methods like word association for exploratory analysis - Developed methods to determine how successful a working group is based on their reports using NLP - Analyzed data given to me using R to answer questions that working group has for NCEAS - Automated certain tasks for NCEAS and its working groups using Python - Wrangled research data into formats more appropriate for analysis using R - Created visualizations using ggplot and used methods like word association for exploratory analysis - Developed methods to determine how successful a working group is based on their reports using NLP - Analyzed data given to me using R to answer questions that working group has for NCEAS - Automated certain tasks for NCEAS and its working groups using Python



Channel Islands YMCA

• Santa Barbara, California Area

• Data Intern

  • May 2018 - Jun 2019

  - Performed k-medians/k-means clustering to create a customer segmentation model to provide fundraising support - Worked on an interactive map for YMCA website using Javascript, HTML, and CSS - Imported and exported data from the Raiser's Edge database - Performed k-medians/k-means clustering to create a customer segmentation model to provide fundraising support - Worked on an interactive map for YMCA website using Javascript, HTML, and CSS - Imported and exported data from the Raiser's Edge database



UCSB Department of Statistics

• Undergraduate Research Assistant

  • Sep 2018 - Apr 2019

  - Organized auto insurance claim adjuster notes into useful data for actuarial analyses and found useful variables that will improve the structured model to predict the severity of bodily injury claims - Used Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) to find the structure and topics of the given notes - Predicted the severity of such claims using SVM, Naive Bayes, Random Forest, Logistic Regression, and Gradient Boosting - Organized auto insurance claim adjuster notes into useful data for actuarial analyses and found useful variables that will improve the structured model to predict the severity of bodily injury claims - Used Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) to find the structure and topics of the given notes - Predicted the severity of such claims using SVM, Naive Bayes, Random Forest, Logistic Regression, and Gradient Boosting



UCSB ICA Baseball Team

• Baseball Analytics Intern

  • Jun 2018 - Nov 2018

  - Performed statistical analysis (i.e hypothesis testing) and logistic regression on the framing of UCSB Catchers to determine what areas the coaches should develop for the upcoming season - Created a web scraper using Python to compile data from numerous websites to find compelling statistics that provides insight towards what wins games in the Big West Conference - Determined the statistical performance drop-off for each of the UCSB starting pitchers in 2018 as they progressed through the opponents order multiple times using 2017 data - Created visualizations for the Director using ggplot - Discussed my findings and reports to the Director of Analytics of UCSB Baseball Show less



AerServ (Acquired by InMobi)

• United States
• Technology, Information and Internet
• 1 - 100 Employee

• Junior QA Developer

  • Jul 2017 - Sep 2017

  - Performed manual regression tests using a spreadsheet of test cases to verify any bugs found in the upcoming update or hotfix - Assisted the EVP of Operations and Technology with data analysis projects using SQL - Wrote and performed automated test cases using Python to detect any bugs - Communicated with tech developers and engineers about upcoming features to develop new test cases for regression/feature testing - Documented and recorded problems and bugs to the tech department using JIRA - Participated in sprint meetings with tech and other departments to provide feedback and discuss the statuses of our tasks, goals, and upcoming deadlines Show less