top of page

About Me

I’m a data-centric professional with 14 years of leadership experience at EY, currently completing my Master’s in Applied Data Science at USC (Dec 2025). This page offers both a downloadable resume and a quick snapshot of who I am — blending business insight with hands-on data and cloud skills.

​

After stepping back in 2024 to support my daughter’s transition into school and refocus my career path, I’ve been sharpening my technical abilities in Python, SQL, AWS, Power BI, and machine learning. My work now spans data engineering pipelines, analytics dashboards, and real-world modeling projects.

​

Thanks for visiting — feel free to download my resume below or scroll down to explore education and experience highlights.

photo-022-c.jpg

Education

Master of Science in Applied Data Science - Expected 12/2025

University of Southern California (USC) • GPA: 3.50

Los Angeles, CA

Master of Business Administration in Finance and Strategic Management

Claremont Graduate University

Claremont, CA​

Bachelor of Science in Biological Science
Bachelor of Arts in Social Science

University of California, Irvine

Irvine, CA​

Work Experience

May 2024 - Present

January 2010 - April 2024

Professional Sabbatical

Data Professional – Independent Study & Technical Training

  • Took planned time off to support my daughter’s successful transition into kindergarten while preparing for re-entry into a more technical data role.

  • Completed graduate-level coursework in machine learning, big data, and cloud analytics using Python, SQL, Spark, and Azure.

  • Built hands-on projects focused on recommendation systems, time series forecasting, and scalable data engineering pipelines.

Ernst & Young

Senior Manager, Tax Technology and Transformation Services

  • Oversaw SaaS and application development projects integrating tax compliance solutions with large-scale datasets.

  • Partnered with clients to scope and deliver custom tools automating tax data analysis and reporting.

  • Led development of custom Python and SQL-based tools to automate tax data analysis and reporting, integrating structured datasets with cloud-hosted platforms.

  • Designed and led implementation of scalable ETL pipelines using SQL and Azure, automating ingestion and transformation of complex tax data across global client systems.

​

Manager, Tax Technology Transformation Services

  • Led a team of 10 consultants on data-intensive tax engagements requiring database and scripting skills.

  • Integrated structured client data into reporting platforms for advanced analytics.

  • Championed process improvement through technology, resulting in faster cycle times for data reviews.

​

Senior Consultant, Business Tax Advisory

  • Conducted interviews with SMEs and used quantitative analysis to support tax credit and deduction positions.

  • Managed full project lifecycle including budgeting, execution, and delivery.

  • Built analytical tools in Excel using pivot tables and charts to support findings.

Relevant Coursework

USC Master's Program

Machine Learning & Recommendation Systems

  • Built classification models using logistic regression, decision trees, SVMs, and ensemble methods.

  • Applied cross-validation and bootstrapping for evaluation.

  • Designed recommendation systems using collaborative filtering, frequent itemset mining, and PySpark.

Big Data & Data Engineering

  • Developed distributed data pipelines using Hadoop and Spark.

  • Performed NoSQL operations with MongoDB, HBase, Firebase, and DynamoDB.

  • Designed and optimized data schemas, integrated data lakes, and explored real-world big data use cases.

Foundations & Python

  • Gained fluency in Python for data science: web scraping, object-oriented design, and visualization.

  • Explored time series, geospatial, and text workflows; studied metadata, ethics, and data provenance.

Skills

Languages

  • Python

  • SQL

Data Systems​

  • AWS EC2

  • DynamoDB

  • Firebase

  • HDFS

  • MongoDB

  • MySQL

Tools / Frameworks

  • Alteryx

  • Hadoop

  • Jupyter Notebooks

  • Matplotlib

  • NumPy

  • Pandas

  • Power BI

  • Scikit-learn

  • Seaborn

  • Spark

  • Tableau

  • XGBoost

Concepts​

  • A/B Testing

  • Big Data Processing

  • Cloud Storage

  • Data Mining

  • Data Pipelines

  • Distributed Systems

  • Feature Engineering

  • Machine Learning:
    ∘ Regression
    ∘ Classification
    ∘ Clustering

  • Metadata & Provenance

  • Model Evaluation

  • NoSQL

  • Recommendation Engines

  • Time Series Analysis

bottom of page