Business Intelligence Analyst, Payments Risk Management

Risk Frameworks and Standards is responsible for the Enterprise Risk Management program for Alphabet; defining and maintaining the Enterprise Risk Management Framework and top line key risk indicators; defining, maintaining inventories of, and driving alignment to standardized policy artifacts and definitions; providing policy oversight to ensure adherence to standards, periodic review and renewal of policies; executing training programs across the company relevant to risk and compliance policies, and defining and ensuring best practices and coherence of business risk assessments.

Payments Risk Management specifically focuses on Payments specific enterprise risks where you get to be on the front line of our regulatory needs. This includes development and enhancement of payments risk management frameworks, policies, assessments, reporting and ongoing needs, all while working cross functionally with teams internally and externally. Additionally, you are thorough in all you do and see to it that as Google pursues our next big idea, we always have our bases covered from a risk perspective.

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Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $116000 - $167000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Collect, analyze, and interpret large datasets related to risk activities.
Develop and maintain key metrics, suggest thresholds, dashboards and reports to visualize the metrics across various different slices and dices of data.
Ensure the accuracy, completeness, and integrity of risk data, and collaborate with engineering partners and other stakeholders to improve data management and validation processes.
Present data insights to both technical and non-technical audiences and contribute to the improvement of risk and compliance processes.
Leverage AI models to enhance capabilities, including for risk assessments and monitoring programs.

Minimum qualifications:

Bachelor's degree in Computer Science, Data Science, Statistics, Finance, or a related field, or equivalent practical experience.
4 years of experience in business intelligence or data analytics.
Experience in data analysis tools and programming languages (e.g., SQL, R, and Google Sheets).

Preferred qualifications:

Experience with data visualization and reporting tools and a strong understanding of data management principles.
Experience in/with enterprise risk management.
Experience with statistical modeling and machine learning.
Strong AI forward thinking and experience with Prompt Engineering.
Excellent analytical, problem-solving, and communication skills.