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Data Analyst, Fraud & Security Expert | Profile 12209

Professional Summary:

An accomplished data science professional specializing in fraud strategy, credit risk, and sales analytics, this Candidate combines expertise in data analysis, machine learning, and strategy implementation to drive operational success and mitigate fraud-related losses. With robust experience in developing and managing analytical models, they excel in cross-functional collaboration, documentation, and process optimization.

Professional Experience Highlights:

Fraud Strategy Development and Implementation

• Designed and managed nearly 100 analytical rules using SQL/SAS for third-party fraud detection, reducing fraud losses by 40+% year-over-year.
• Partnered across departments to respond rapidly to fraud threats, ensuring swift mitigation.
• Trained new hires on fraud detection principles and analytical best practices, enhancing team proficiency and preparedness.
• Monitored and maintained team’s internal data sources, making code improvements as necessary to address evolving business needs.

Data Analysis and Feature Engineering

• Leveraged SQL/SAS to analyze fraud trends and engineer new features to strengthen fraud detection strategies.
• Led weekly case review meetings, identifying strategy gaps and emerging fraud trends.
• Assisted the deposits team in addressing fraud attacks, conducting feature engineering, developing strategies, and establishing standard case review processes.
• Oversaw daily and monthly team metrics reporting, ensuring accurate data tracking and insight generation.

Credit Risk Strategy and Reporting

• Automated a suite of Tableau dashboards to monitor acquisition strategies, enhancing data visibility and decision-making.
• Drafted standard work instructions for critical processes, contributing to operational consistency.
• Conducted impact analyses on acquisition portfolios, including effects from COVID-19 and economic downturns, to optimize risk strategies.

Model Evaluation and Analytics in Credit Risk

• Compared linear regression and Gradient Boosting Machine models for customer line increase requests, analyzing strategic and profitability impacts.
• Utilized SAS and SQL to evaluate model performance, ensuring effective decision-making support.

Sales and Marketing Data Analytics

• Analyzed Salesforce sales pipeline data, developing visualizations to support sales operations.
• Leveraged R/SQL to identify productive marketing interactions, contributing to enhanced sales opportunities.

Technical Proficiencies:

Highly Proficient In:

• R (Shiny, ggplot2, dplyr)
• SQL, Tableau, Airflow, SAS Enterprise Miner, SAS Financial Management

Intermediate Skills In:

• Python (pandas, NumPy, scikit-learn), Teradata, Stata, GitHub

Familiarity With:

• Salesforce, AWS, Hadoop, Spark, Google Cloud Platform, C++

Education:

Bachelor of Science in Business Administration

• Majors in Data Analytics and Quantitative Economics, Minor in Mathematics
• Graduated magna cum laude

This Candidate’s blend of technical skill, strategic insight, and dedication to fraud prevention and data analytics makes them an invaluable asset to any team focused on data-driven decision-making and risk mitigation.

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