Business Data Scientist, Internal Audit bei Google
Google · Chicago, Vereinigte Staaten Von Amerika · Onsite
- Professional
- Optionales Büro in Chicago
Minimum qualifications:
- Bachelor's degree in a STEM field or equivalent practical experience.
- Experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
- 4 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.
- 4 years of experience in risk, AI safety, or a domain focused on identifying, quantifying and mitigating varied harms.
- Experience applying GenAI to data analysis problems for data generation, enrichment or scaled processing.
About the job
Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
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.
Responsibilities
- Partner with business, technology, privacy and security auditors, work 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. 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.
