Shixuan Song - Risk Data Analyst (Financial Crime)

Shixuan Song

Risk Data Analyst (Financial Crime)

Boston, Massachusetts, United States

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Summary

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Rockstar

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Top School

Shixuan Song is a risk data analyst in PwC’s Cyber, Risk, and Regulatory practice with eight years of analytical experience and over two years focused on anti-money laundering work for major financial institutions. She blends strong SQL and Tableau skills with Azure SQL experience to validate data quality for millions of transactions and map hundreds of attributes during AML model migrations. Her background in building exploratory data analysis features for an open-source Python dataprep library shows she balances practical client delivery with contributions to tooling that improve correlation and missing-value insights. Comfortable coordinating multi-workstream agile teams, she partners with product owners to translate technical findings into actionable controls and recommendations. With a Data Science master’s from NYU and a track record improving model performance and donor targeting in prior roles, she combines statistical rigor with a knack for turning messy data into measurable business outcomes.

8 years of coding experience

3 years of employment as a software developer

Bachelor of Science - BS, Statistics, Certificate in Business and Mathematics, 3.74/4.0, Bachelor of Science - BS, Statistics, Certificate in Business and Mathematics, 3.74/4.0 at University of Wisconsin-Madison

Master's degree, Data Science, Master's degree, Data Science at New York University

Statistics, 3.97/4.0, Statistics, 3.97/4.0 at University of Connecticut

English, Chinese

Stackoverflow

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Github Skills (13)

data-visualizations10

data-preprocessing10

pandas10

data-visualisation10

data-visualization10

dataprep10

data-exploration10

bokeh10

exploratory-data-analysis10

python10

numpy10

eda10

data-cleaning9

Programming languages (2)

C++Python

Github contributions (5)

sfu-db/dataprep

Jun 2019 - Nov 2021

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

Role in this project:

Data Scientist

Contributions:70 commits, 22 PRs, 16 pushes in 2 years 5 months

Contributions summary:Shixuan primarily contributed to the development of exploratory data analysis (EDA) functionalities within the data preparation library. Their work involved implementing methods for calculating and visualizing correlations, including Pearson, Spearman, and Kendall correlation matrices, and creating related visualizations. They also implemented features for missing value analysis, specifically for identifying missing value locations and their impact on the data. Furthermore, the user enhanced existing visualizations within the library.

pythondatadataprepcleaningdatacleaning

YunzeMan/Mini-Operating-System

Nov 2017 - Jan 2018

Contributions:28 commits, 25 pushes, 1 branch in 2 months

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