- Sunnyvale, CA
- Full-Time
- 7 days ago
Business Data Scientist, Internal Audit.
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Business Data Scientist, Internal Audit: our view in 3 lines...
- The Role:This role is for a business data scientist in Internal Audit who focuses on risk across Alphabet.
- The Person:The person will analyze product, infrastructure and financial data, identify and quantify risk, evaluate controls, develop repeatable methods and infrastructure, and convey findings to stakeholders.
- Requirements:The ideal candidate has a quantitative degree, experience applying GenAI to data analysis problems, and experience using analytics, coding, querying databases, or statistical analysis.
About the role
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.
About the job:
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $116000 - $165000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
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.
