Senior Associate, Risk Analytics

Summary

Gemini is a global crypto and Web3 platform providing secure access to digital assets and financial services. The company is seeking a Senior Associate, Risk Analytics to design and implement automated continuous control monitoring and agentic AI systems across enterprise risk domains. The role will develop risk analytics, predictive models, dashboards, and AI-driven workflows while collaborating with Engineering, Data, Compliance, Operations, and Product teams.

Responsibilities

• Continuous Control Monitoring + Lead the design and implementation of an automated, continuous monitoring framework that spans all enterprise risk domains (Credit, Fraud, Operational, Compliance). Move the firm away from periodic/manual checks toward real-time observability
• Agentic Risk Infrastructure + Scale our risk management capabilities by developing and deploying AI agents to monitor control activities. Orchestrate agentic workflows to perform proactive anomaly detection, perform root-cause analysis on incidents, and suggest risk mitigation actions
• Enterprise Risk Analytics + Interpret large, complex datasets to formulate problem statements and generate insights across all business verticals. Develop predictive models and detection tools that reduce risk exposure and enhance operational efficiency
• Risk Governance & Reporting + Maintain a comprehensive view of the AI and model risk inventory. Develop automated dashboards that provide senior management with a "solid analytical story," leveraging BI tools to track Key Risk Indicators (KRIs) against appetite
• Cross-Functional Collaboration + Partner with the Risk Engineering, Identity, and Product teams to ensure risk telemetry is properly instrumented. Provide clear communication and training on how to interpret agentic outputs and maintain human-in-the-loop oversight

Skills

• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Finance, Engineering)
• 3–5 years of experience in risk management, analytics, or a related technical domain
• Technical Proficiency: Strong SQL and relational database skills; intermediate-to-advanced Python ability
• AI/Agentic Frameworks: Demonstrated experience or strong familiarity with building or deploying AI agents (e.g., LangChain, AutoGen, or similar orchestration frameworks) and large language model integration
• Continuous Monitoring: Experience designing or maintaining automated systems for data quality, observability, or control monitoring
• Data Communication: Ability to translate complex data and AI output into clear, actionable reporting for senior stakeholders
• Mindset: A "no-task-is-too-small" attitude, combined with the ability to operate in ambiguity and a healthy balance of empathy and skepticism toward automated systems
• All employees, however, are required to onboard in-person at one of our office locations
• Experience with Business Intelligence and Data Visualization (Tableau, Looker)
• Prior experience in model risk management (MRM) and knowledge of MAS AI MRM supervisory expectations
• Experience with AWS Bedrock, GCP and opensource LLMS
• Experience in MLOps or AIOps (e.g., CI/CD pipelines for AI/ML models)

Qualifications

Must Haves

• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Finance, Engineering)
• 3–5 years of experience in risk management, analytics, or a related technical domain
• Technical Proficiency: Strong SQL and relational database skills; intermediate-to-advanced Python ability
• AI/Agentic Frameworks: Demonstrated experience or strong familiarity with building or deploying AI agents (e.g., LangChain, AutoGen, or similar orchestration frameworks) and large language model integration
• Continuous Monitoring: Experience designing or maintaining automated systems for data quality, observability, or control monitoring
• Data Communication: Ability to translate complex data and AI output into clear, actionable reporting for senior stakeholders
• Mindset: A "no-task-is-too-small" attitude, combined with the ability to operate in ambiguity and a healthy balance of empathy and skepticism toward automated systems
• All employees, however, are required to onboard in-person at one of our office locations

Nice to Haves

• Experience with Business Intelligence and Data Visualization (Tableau, Looker)
• Prior experience in model risk management (MRM) and knowledge of MAS AI MRM supervisory expectations
• Experience with AWS Bedrock, GCP and opensource LLMS
• Experience in MLOps or AIOps (e.g., CI/CD pipelines for AI/ML models)

Benefits

• A discretionary annual bonus
• Long-term incentive in the form of a new hire equity grant
• Comprehensive health plans
• 401K with company matching
• Paid Parental Leave
• Flexible time off
• In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Employees who do not live near one of our hubs are part of our remote workforce.