• Manage HMDA and CRA data integrity reviews, including routine monitoring, exception tracking, and remediation. • Coordinate the annual HMDA Loan/Application Register (LAR) and CRA data submission processes. • Perform data validation and quality control testing to identify coding, completeness, and accuracy issues. • Partner with Compliance, Operations, Engineering, and other business teams to resolve data discrepancies. • Maintain documentation of data reviews, corrections, procedures, controls, and submission evidence. • Support regulatory exams, internal audits, compliance testing, and investor or management reporting related to HMDA and CRA. • Monitor regulatory changes and assist with updates to policies, procedures, training, and system controls. • Prepare periodic reporting for management on data quality trends, exceptions, corrective actions, and submission readiness.

• Own the analytics infrastructure for GroweLab — designing and maintaining dashboards and reports that surface platform usage, engagement trends, feature adoption, and learner progress. • Partner with the Product Manager to provide data that informs GroweLab’s roadmap, prioritization decisions, and feature performance evaluation. • Work with the QA Analyst and engineering team to ensure data pipelines are accurate, reliable, and well-governed across GroweLab’s systems. • Translate platform data into clear, actionable insights for product, delivery, and leadership teams. • Lead the analytical interpretation of e2L’s survey and measurement tools — translating results into insights partners can act on. • Develop partner-facing reporting frameworks that demonstrate e2L’s impact on educator growth, instructional practice, and student outcomes. • Build and maintain visualizations and reports that make complex outcome data accessible to district leaders and school administrators. • Collaborate with the Solutions Analyst to design data solutions that address specific partner needs and questions. • Serve as the data resource for new product and feature development — ensuring that measurement, tracking, and reporting are built into the design of e2L’s tools from the start.

Role Description We're looking for a Data Analyst to partner closely with our Customer Success and GTM teams and turn data into decisions. You'll own the metrics that matter — acquisition, activation, retention, product usage, expansion, and revenue — and uncover the drivers behind them. You'll build the analyses that shape strategy, identify what influences customer success and growth, and help answer the critical questions: what's working, what isn't, and why. This is a high-ownership, hands-on role for someone who loves digging into data, writes their own code, and ships analysis that changes what the business does next. What You'll Do - Own GTM analytics end-to-end: define, instrument, and report on the funnel — from signup and activation through conversion, expansion, and churn. - Proactively monitor key business metrics, investigate trends and anomalies, and surface actionable insights to stakeholders. - Partner with other teams like Sales, Marketing and Product to scope questions, run analyses, and translate findings into clear recommendations. - Dig into product usage and revenue data to surface insights on user behavior, cohorts, and monetization. - Write production-quality SQL and Python to model data, automate pipelines, and run analyses at scale. - Design and evaluate experiments (A/B tests) and measure the impact of GTM initiatives. - Define metrics and a shared source of truth; bring rigor and clarity to how we measure success. Qualifications - 5+ years of experience as a Data Analyst (or equivalent). - 2+ years working in a SaaS company. - Hands-on experience as a CS / Sales / Marketing / Business / Product analyst — you understand funnels, cohorts, conversion, retention, and the metrics that drive a SaaS business. - Strong hands-on experience using Python for data analysis, experimentation, and data modeling in a production environment. - Strong SQL and comfort working with large, messy datasets. - Strong communication: you can turn analysis into a clear, compelling story for non-technical stakeholders. - Statistical foundation for experimentation and causal inference. - BSc in Statistics/Math/CS or equivalent. - Familiarity with modern data tooling (Snowflake/BigQuery, dbt, Airflow, BI tools like Omni/Looker/Tableau). - Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders. Requirements - A track record of building your own projects - a GitHub profile, portfolio, side projects, or other evidence that you build things independently. - Experience at an API-first, developer-focused, or PLG (product-led growth) company. - Experience with product analytics platforms (PostHog, Amplitude, Mixpanel). - Exposure to ML or working alongside data science teams. - MSc in Statistic/Math/CS or equivalent. Benefits - Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. - 401(k) plan: Up to 4% company match with immediate vesting. - Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. - Remote work reimbursement: Up to $85/month for mobile and internet. - Disability & life insurance: Company-paid short-term, long-term and life insurance coverage. - Competitive salaries, ranging from $109,500 - $172,000 OTE based on your experience. - Pay Transparency: Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. - Benefits & Perks: Competitive compensation, career growth and learning opportunities, flexibility and ownership, collaborative and innovative culture, opportunity to work on impactful AI projects, international environment and talented teams. Equal Opportunity Statement Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

• Articulate and execute against data & analytics vision in support of Accounting, Finance and other business teams as needed, including development of Accounting Data and Analytics roadmap • Partners with FP&A, Record-to-Report, Procure-to-Pay, Order-to-Cash, Tax, and Treasury teams to maintain a strong understanding of the key business drivers, specific business processes and analytics priorities • Lead deep exploration of financial, customer, product, sales, and support data and communicate actionable analysis/insights to stakeholders • Spearhead the development and deployment of AI solutions in Finance to optimize decision-making and operational efficiency • Deliver insights and provide actionable recommendations based on reported results, benchmarks, discovered patterns, and other necessary context • Facilitate and drive the successful completion of data insight initiatives in line with aligned roadmap by effectively managing data analysts and collaborating with stakeholders • Develop in-depth understanding of key data sources and data lineage within the organization and data warehouse and effectively leverage knowledge to derive meaningful analytics results • Support enterprise data roadmap by managing the accounting function’s data model, data mart(s), user access, and adoption of advanced analytics capabilities in line with overall company data strategy • Facilitate best practices discussions with business, as needed to develop functional competencies and foster data-driven culture, and continuously improve the quality, consistency, accessibility, and security of accounting data • Lead, mentor, and develop a high-performing team of data analysts to achieve functional and professional growth • Cultivate a dynamic environment of continuous learning, innovation, and cross-functional collaboration.