• Be on the cutting edge of structured finance and technology. You will be a critical piece in dv01's robust expansion into the capital markets and structured finance space, combining your knowledge with our state-of-the-art technologies. • Expand your structured finance knowledge. You will gain exposure to many facets of the ABS and RMBS spaces, combining information from a variety of sources (loan-level transaction data, deal documents, trustee reporting, etc.) that all flow into dv01's wide range of client offerings. • Enhance your technical skills. You will work closely with engineering teams at dv01 to develop and productize solutions, both for our customers and internally. If you're not already aware of the world that exists outside of Excel for data analysis, you'll become familiar with it very quickly. • Be customer-facing. You will directly communicate with contacts at hedge funds, banks, and asset originators, providing valuable reporting and analytics services to assist with their internal processes.

• Write, maintain, and optimize SQL queries in BigQuery to support reconciliation and data validation workflows • Lead end-to-end data reconciliation amongst or partnering law firms • Identify and resolve data inconsistencies in partnership with internal teams and external partners • Proactively monitor data automations in place with our partnering law firms • Improve, document, and standardize data processes, quality-control measures, and workflows to drive continuous improvement projects • Create dashboards and reporting to help drive actionable insights for larger teams • Mentor, train, and guide other team members on data best practices

• Support design and monitoring of EWA underwriting strategies and forecasting tools. • Translate analytical findings into clear recommendations for credit policies. • Support champion/challenger tests and experiment design for EWA risk strategies. • Assist in designing exposure limits, eligibility rules, and verification checks. • Query, clean, and analyze large bank transaction datasets using SQL and Python, or R/SAS). • Build dashboards, reports and durable data assets to track customer behavior and credit performance. • Perform EDA, feature engineering, and data quality checks to drive trusted insights. • Prepare model inputs, evaluate new data sources (including open-banking data), and track model performance. • Analyze performance of underwriting strategies and identify opportunities to improve accuracy and reduce losses. • Learn and introduce new analytical tools and techniques relevant to credit risk. • Partner with Product, Engineering, Data Science, and Operations to implement updates to policies and decisioning logic. • Support the coordination of initiatives with data suppliers. • Package insights into crisp narratives and presentations for stakeholders.

• Participating in discovery and requirements sessions to understand business goals and translate them into tracking plans • Collaborating with developers and the Analytics Lead to design and document data layer specifications for GA4 tracking • Implementing and validating events using Google Tag Manager, including tag configuration, triggers, variables, and testing • Configuring and maintaining Google Analytics 4 properties, including events, parameters, custom dimensions, and conversions • Troubleshooting and validating tracking with debugging tools such as GA4 DebugView, Tag Assistant, or similar tools • Supporting GA4 data exports and modeling within BigQuery to structure data for reporting and analysis • Building reports and dashboards using Looker Studio or other visualization tools to communicate insights • Performing quality assurance, audits, and ongoing maintenance to ensure accurate and consistent measurement • Collaborating with media, strategy, and development teams to ensure analytics aligns with overall business objectives • Supporting documentation, tagging governance, and measurement frameworks • Staying current with analytics best practices, privacy standards, and updates across the Google ecosystem