Account Receivable Accountant
About Nebius
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Role Overview
The Accounts Receivable Accountant will be responsible for driving data-based insights, automation, and analytical excellence within the Accounts Receivable (AR) domain.
This role plays a key part in strengthening financial accuracy, improving receivables processes, and supporting strategic decision-making across Finance.
The AR Accountant will independently manage end-to-end analytical processes — from data modeling and reconciliation automation to performance reporting — while partnering with cross-functional stakeholders to ensure data integrity and operational efficiency.
Key Responsibilities
Analytical & Strategic Finance Support
- Analyze AR and revenue data to identify patterns, forecast trends, and highlight process improvement opportunities.
- Develop dashboards and analytical models to monitor receivables health, DSO performance, and collection efficiency.
- Provide actionable insights and recommendations to support strategic decision-making in Finance and Business Operations.
Process Optimization & Automation
- Design, implement, and maintain automated AR data workflows and reconciliation
- Partner with Accounting and Engineering teams to streamline data pipelines between ERP (NetSuite) and reporting systems.
- Continuously improve data accuracy, reconciliation speed, and operational efficiency through automation and analytical solutions.
Reporting & Data Visualization
- Develop and maintain BI dashboards and reports (e.g., Power BI, Tableau, or Looker) providing visibility into receivables, revenue timing, and intercompany
- Translate complex financial data into clear and concise management
- Support monthly and quarterly closing with data validation, variance analysis, and reconciliation analytics.
Cross-Functional Collaboration
- Partner with Accounting, Treasury, and Business Operations teams to ensure consistent AR data definitions and accuracy.
- Collaborate with Data and Engineering teams to enhance system integrations and data quality.
- Contribute to financial systems improvements and new tool
Governance & Compliance
- Ensure data integrity and compliance with accounting principles and internal
- Support audit and compliance requirements through data-driven reconciliations and reporting traceability.
Key Qualifications & Experience
Must-have requirements
- Bachelor’s or Master’s degree in Accounting, Finance, Economics, or Data
- 4–6 years of experience in Finance, Accounting, or Data Analytics with a focus on AR or revenue processes.
- Strong analytical background with proficiency in SQL and Excel (advanced functions, pivot tables, modeling).
- Experience with BI tools (Power BI, Tableau, or similar).
- Knowledge of ERP systems (preferably NetSuite) and data integration
- Working knowledge of US GAAP or IFRS accounting
- Ability to independently identify issues, propose solutions, and drive process
- Excellent communication skills with the ability to explain analytical results to non-technical audiences.
- Fluency in English (written and spoken).
Preferred qualifications
- Experience in a multinational or technology-driven finance
- Familiarity with tax reporting and intercompany
Competencies & Behavioral Traits
- Strong analytical and critical thinking
- Proactive problem-solving and ownership
- Structured approach to managing complex datasets and
- Ability to translate data into strategic business