Risk Data Analyst

About the opportunity

Description At R2, we believe that small and medium businesses are the productive engine of society. Small and medium businesses (SMBs) make up over 90% of companies in Latin America, yet they face a trillion-dollar credit gap. Our mission is to unlock SMBs’ potential by providing financial solutions that are tailored to their needs. We are reimagining the financial infrastructure of Latin America, where SMBs’ financial needs are satisfied without ever having to go to a bank. R2 enables platforms in Latin America to embed financial services that SMBs can then leverage (starting with revenue-based financing). We are a tight-knit team coming from organizations such as Google, Amazon, Nubank, Uber, Capital One, Mercado Libre, Globant, and J.P . Morgan. We are entering a new phase of growth following a strategic investment from Ant International, focused on rapidly expanding our partner footprint, strengthening our credit and underwriting capabilities, and scaling our operations across multiple markets. R2 is scaling quickly, and with that growth comes increasing operational complexity. We are looking for a hands-on Risk Sr Data Analyst (IC3) to help build, automate, and validate the controls that keep our operations reliable as we scale. This is a highly technical, execution-focused role for someone who is comfortable working directly with data: writing SQL to interrogate our systems, scripting in Python to automate control testing, and building dashboards that make risk and control performance visible in real time. This person will turn control requirements into working, testable, automated checks — not slide decks or policy documents alone. The right candidate is analytical, technically fluent, and energized by taking an ambiguous process and turning it into a monitored, data-driven control that runs itself. Key Responsibilities • Implement, execute, and maintain preventive, detective, and monitoring controls across key business and operational processes. • Write SQL to query production and analytical data sources to test controls, pull audit evidence, and investigate exceptions across large datasets. • Build and maintain Python scripts and automated routines that test controls on a recurring basis, flag exceptions, and generate reproducible results. • Design and build control-monitoring dashboards and KPI reporting (e.g. Tableau) so control health and risk indicators are visible to stakeholders. • Translate control designs and process requirements into concrete, automated checks and validation logic. • Validate that controls are operating as intended: define test cases, run them against real data, quantify exceptions, and document results. • Analyze workflows and data to identify control gaps, failure points, manual dependencies, and areas of elevated operational risk. • Partner with Risk, Product, Operations, Finance, Compliance, Technology, and Data teams to embed automated controls into system workflows and daily operations. • Maintain clear documentation of control logic, test procedures, data sources, and results to support internal and external review. • Track control exceptions and issues through to remediation, and re-test to confirm closure. • Apply a solid understanding of risk and control principles (including COSO-based thinking) to ensure the controls you build are meaningful and auditable. • Operate with high ownership in an environment that is still building process discipline and tooling maturity. Requirements What We’re Looking For • 3–6 years of experience in a technical, data-driven role such as risk/data analytics, controls testing, internal audit analytics, data analysis, or a related field. • Strong, hands-on SQL skills — able to independently write and optimize queries against large datasets to test controls and analyze exceptions. • Working proficiency in Python for automating control tests, building validation scripts, and data analysis (e.g., pandas). • Experience building dashboards and reporting in a BI tool such as Looker, Tableau, or Power BI. • Demonstrated ability to translate a process or control requirement into automated, testable logic — this is a builder role, not an advisory one. • Understanding of internal control concepts and frameworks such as COSO, and how to test controls for design and operating effectiveness is nice to have. • Strong analytical judgment: able to spot anomalies in data, quantify risk, and separate signal from noise. • Comfortable working with ambiguity and limited structure, and turning it into repeatable, documented processes. • Excellent written and verbal communication skills, with the ability to explain technical findings clearly to non-technical stakeholders. • Experience in fintech, lending, payments, or another regulated financial services environment is strongly preferred. • Familiarity with data pipelines, version control (Git), or workflow automation is a plus. Benefits What We Offer • The chance to join a high-impact, mission-driven fintech with regional scale. • Ownership of the tooling and automation behind R2’s control environment in a fast-paced, growth-oriented startup. • Cross-functional collaboration with exceptional teams across Latin America. • Exposure to complex regulatory challenges and innovation in embedded finance. Locations BR, AR

Responsibilities

• • Implement, execute, and maintain preventive, detective, and monitoring controls across key business and operational processes.
• • Write SQL to query production and analytical data sources to test controls, pull audit evidence, and investigate exceptions across large datasets.
• • Build and maintain Python scripts and automated routines that test controls on a recurring basis, flag exceptions, and generate reproducible results.
• • Design and build control-monitoring dashboards and KPI reporting (e.
• Tableau) so control health and risk indicators are visible to stakeholders.
• • Translate control designs and process

Qualifications

• into working, testable, automated checks — not slide decks or policy documents alone.
• The right candidate is analytical, technically fluent, and energized by taking an ambiguous process and turning it into a monitored, data-driven control that runs itself.
• into concrete, automated checks and validation logic.
• • Validate that controls are operating as intended: define test cases, run them against real data, quantify exceptions, and document results.
• • Analyze workflows and data to identify control gaps, failure points, manual dependencies, and areas of elevated operational risk.
• • Partner with Risk, Product, Operations, Finance, Compliance, Technology, and Data teams to embed automated controls into system workflows and daily operations.
• • Maintain clear documentation of control logic, test procedures, data sources, and results to support internal and external review.
• • Track control exceptions and issues through to remediation, and re-test to confirm closure.