Senior Financial Risk Analyst

Unchain Data; California; Hybrid; USD 86,000 - 130,000; Full time

Job summary

Unchain Data is seeking a financially curious professional to help manage liquidity risks, build data-driven models, and deliver dashboards and alerts for treasury functions. You will collaborate with Data Science and Engineering teams to surface capital and counterparty risks.

The role demands strong analytical skills, knowledge of macroeconomics and financial markets, and the ability to turn complex findings into actionable processes.

Qualifications

• Bachelor's degree in mathematics, computer science, engineering or a related field is required.
• 1–3 years of experience in data analytics, risk management, or a similar analytical role.
• Strong quantitative and communication skills to convey complex findings to non-technical stakeholders.
• Solid grounding in financial risk methodologies like VaR, stress testing, scenario analysis, and attribution modeling.

Responsibilities

• Monitor daily financial risks across the firm and escalate material exposures.
• Conduct deep-dive quantitative analyses into liquidity risks across the organization.
• Enhance and maintain liquidity risk models and forecasting frameworks.

Skills

SQL

Python

Data analytics

Risk management

Communication

Problem solving

Education

Bachelor's degree in mathematics, computer science, engineering or a related field

Tools

Airflow

Looker

Superset

Job description

About Us

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you're ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the Role

We are looking for an intellectually curious and enthusiastic individual to help the organization prepare for continued rapid growth by having a good understanding of the impact of the financial markets and risks on Robinhood. This role is responsible for monitoring corporate liquidity risks and investments, developing financial risk models, forecasting key balance sheet items and providing deep dive analysis into financial market drivers of the business.

This role suits those with a bias towards action and impact, who believe in end to end execution and accountability. You are the perfect mix of analytical, technical, operational, and creative. You are a clear, confident communicator who loves taking a complicated problem, decomposing it, and building data driven models, then turning those models into processes and reports.

Responsibilities

• Monitor and report on financial risks across the firm on a daily basis, ensuring timely escalation of material exposures
• Conduct deep-dive quantitative analyses into liquidity risks emerging across the Robinhood ecosystem
• Enhance and maintain liquidity risk models and forecasting frameworks to support proactive risk management
• Partner with Data Science and Engineering teams to design and deliver dashboards, automated alerts, and data pipelines that surface capital, liquidity, and counterparty credit risks for the Treasury function
• Collaborate with Finance and Product teams to assess emerging risks associated with new products and business initiatives

Requirements

• Bachelor's degree in mathematics, computer science, engineering or a related field
• 1–3 years of experience in data analytics, risk management, or a comparable analytical role
• Strong quantitative and problem-solving skills, with the ability to communicate complex findings clearly to non-technical stakeholders
• Solid grounding in financial risk methodologies including Value-at-Risk, stress testing, scenario analysis, and attribution modeling
• Understanding of macroeconomics, financial markets, financial instruments, trading strategies, and investment theory
• Advanced proficiency in SQL and Python
• Ability to build and own process from the ground up
• Demonstrated ability to design and own end-to-end processes in ambiguous, fast-moving environments

Nice to Have

• Advanced graduate degree such as an MFE or in a similar technical field
• Experience developing and deploying production-grade financial models in Python or R
• Familiarity with sophisticated financial instruments including derivatives, futures, leveraged products, and digital assets
• Experience with time series modeling and regression techniques
• Hands-on experience with AI/ML tooling and business intelligence platforms such as Superset or Looker
• Working knowledge of ETL pipelines and workflow orchestration tools such as Airflow

Compensation

In addition to the base pay range listed below, this role is also eligible for bonus opportunities, equity, and benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC): $111,000—$130,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL): $97,000—$114,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL): $86,000—$101,000 USD