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Junior Product Operations Analyst

• Provide support to clients through different channels.
• Assist in the daily operational processes that connect Product, Finance, and Operations and comply with SLA.
• Support data validation and reconciliation tasks to ensure accuracy across systems.
• Collaborate with the Product and Engineering teams to identify process improvements and automation opportunities.
• Help build and maintain dashboards and reports to track key business and operational metrics.
• Contribute to the implementation of new product features from an operational and financial perspective.
• Participate in testing and validating new tools or processes before rollout.
• Support the creation and documentation of standard operating procedures (SOPs).
• Help identify inefficiencies and propose data-driven solutions to enhance our internal operations.

Product Operations Intern – LATAM

Marketing Operations

• Spearhead the structuring and scaling of R2’s Marketing data infrastructure.
• Collaborate cross-functionally with Product, Engineering, Growth, and partner teams to build the systems that power marketing attribution, operational execution, and real-time performance visibility across all R2 partnerships.
• Own the end-to-end marketing data layer, from ingestion to dashboards to operational execution.
• Connect and maintain marketing data sources (Customer.io, Snowflake, partner files, APIs), ensuring data freshness, correctness, and reliability.
• Build near-real-time attribution dashboards that connect campaigns to applications and originations.
• Design and manage reporting systems in tools such as Looker, Tableau, Metabase, or similar BI platforms.
• Enable real-time detection of underperformance and anomalies across partners and campaigns.
• Manage manual operational workflows while we automate them, including: Generating and uploading CSV datasets, Uploading offer campaigns into our Backoffice, Extracting complex ad hoc reports, Ensuring correct segmentation in Customer.io.
• Support marketing experimentation by analyzing performance across segments (amount, risk tier, geography, partner) and providing structured inputs for A/B tests, cadence adjustments, and campaign extensions.
• Work with APIs and automation tools to improve the integration between Snowflake, Customer.io, and external partner systems.
• Progressively eliminate manual bottlenecks and drive toward fully automated marketing operational workflows.
• Responsible for building a real-time observability dashboard showing how Marketing drives originations at R2.

Senior Product Marketing Ops

Product Manager

• You will own the end-to-end roadmap and execution of R2’s GenAI platform capabilities, in close partnership with the Director of Product.
• You will take ownership of scaled or operationally complex partner integrations once they mature beyond initial launch, ensuring long-term sustainability and standardization.
• You will maintain and scale R2’s GenAI stack, including internal agents, orchestration layers, shared infrastructure, and platform tooling.
• You will translate internal business use cases (Risk, Collections, Support, Marketing, Ops, etc.) into reusable, productized GenAI components.
• You will ensure GenAI/Platform capabilities are: Standardized across teams, technically consistent, scalable by design, secure, observable, and measurable.
• You will define prioritization frameworks for product initiatives and align stakeholders across teams that depend on shared infrastructure, working closely with Engineering to build, test, and deploy solutions.
• You will work closely with Engineering to define architecture decisions, guardrails, and performance standards for Product initiatives.
• You will drive cross-functional coordination across Product, Engineering, Risk, Collections, Support, and Marketing to ensure platform leverage rather than duplicated effort.
• You will identify fragmentation risks across agents, infrastructure, and integrations, and proactively centralize patterns and best practices.
• You will ensure documentation, internal enablement, and governance mechanisms are in place for GenAI and partner platforms.

Senior Product Manager

Full-stack Engineer

• Design, build, and maintain APIs, services, and systems across R2
• Own the product and solution architecture
• Ensure best practices and uptime
• Contribute to company-wide standards and reliability
• Ensure delivery of mission-critical systems with tight deadlines
• Increase the quality of the delivered code, towards a zero-bug policy
• Research and invest in new tooling to improve services
• Think about security throughout everything you do
• Promote a culture that fosters learning, growth, risk taking, and accountability
• Work with other teams to figure out how to build tools to make them more productive

Product Engineer

Technical Product Manager

• Own ensuring everyone is set up to use and actually leverages data across the company via queries, dashboards, and alerts.
• Manage week-to-week prioritization of data engineering and data science teams by identifying critical data dependencies, removing technical roadblocks, and ensuring efficient execution of workflows and OKRs.
• Lead the deployment and integration of scalable systems to automate key processes (e.g. ERP -> financial workflows and reporting).
• Enhance and automate processes for seamless, automated transaction processing.
• Improve cross-functional workflows when integrating new partners, including QA implementation of our underwriting system and Risk analyses, while managing global timelines.
• Define and measure technical success metrics, providing clear reporting on project progress, system performance, and business impact.

Technical Program Manager – TPM

Machine Learning Engineer

• Own ML systems & tooling in production
• Define and evolve R2’s ML platform architecture
• Architect, implement, and deploy ML/DL models into production environments
• Design and build automated monitoring systems to track model performance
• Develop frameworks to automate recurrent Data Science workflows
• Partner with Product, Engineering, and Risk teams to align ML/DL solutions with business goals
• Mentor junior and senior data scientists and analysts