Engineering Analyst Job in Hyderabad at Google

Google is hiring for the role of Engineering Analyst!

Responsibilities of the Candidate:

• Promote user trust and safety, managing and mitigating payment fraud and abuse for Google products and services. Investigate fraud and abuse incidents and identify patterns and trends to generate risk management solutions.
• Perform statistical analysis using payments and risk data warehouses. Collaborate with Engineering and Product teams to create and enhance tools, develop signals, and improve system functionality, accuracy, and efficiency.
• Perform assessment for the riskiness and vulnerability of products and features, design and implement fraud and abuse mitigation strategies.
• Engage and collaborate with cross-functional teams globally, and work closely with Engineers, Product Managers, and various internal and external stakeholders to launch risk mitigation solutions.
• Participate in the on-call rotation schedule to manage escalations that may occur outside of standard non-working hours including weekends/holidays.

Requirements:

• Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research), or equivalent practical experience.
• 2 years of experience in data analysis or a data science setting.
• Experience with programming languages (e.g., Python, R, Julia) and database languages (e.g., SQL).
• Preferred Qualifications:
  • Master’s degree or PhD in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.).
  • 2 years of experience in the Payments industry, working on risk or fraud management.
  • Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript) and/or data-focused programming.
  • Experience working with Large Language Models (LLMs).
  • Knowledge of one or more of the following areas: Statistical analysis and Machine Learning libraries (e.g., R, Scikit-learn, Tensorflow), Programming languages (e.g., Python, C/C++), Large Language Models (LLMs), or Generative AI.
  • Ability to generate actionable insights to drive business impact.