Business Data Scientist, Internal Audit

Role Overview

Internal Audit‘s mission is to focus on reducing risk across Alphabet. We do this by monitoring the risk environment across Alphabet and providing insights to enable effective risk management. We work closely with teams and leadership to achieve a strong control environment that enhances and protects organizational value. We serve as one of the company’s various lines of defense for staffing and developing our team to be control experts who deliver objective and reliable results.

As a member of the team, you will advise the business and engineering groups to identify areas of risk and make valuable recommendations on controls. You will have the opportunity to influence change and decisions for business initiatives including product launches and system implementations. You enjoy working in a dynamic environment, are passionate about technology and are able to focus on key issues and the details that come with it.

Responsibilities

• Partner with business, technology and privacy and security auditors, working closely with cross-functional teams including engineering, product management, operations and finance to identify and quantify risk, as well as to evaluate controls at scale.
• Analyze product, infrastructure and financial data for a variety of patterns including abuse, fraud, brand risk, control breakdown and regulatory non-compliance; succinctly calibrate and convey findings from your work to varied stakeholders.
• Develop repeatable methods to ensure consistent results. Develop infrastructure to support analyses and automate audit procedures.
• Influence teams towards data-informed decision-making and analytical thinking.

Requirements & Qualifications

Minimum qualifications:

• Bachelor's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• Experience applying GenAI to data analysis problems for data generation, enrichment, or processing.

Preferred qualifications:

• 2 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

Application Instructions

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