Billing Data Analyst

Ruby Labs is a leading tech company that creates and operates innovative consumer products across the health, education, and entertainment industries.

• Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
• Experience as a Data Analyst, ideally within fintech, subscription products, billing, or customer support.
• Strong SQL skills.
• Experience with popular BI tools such as Tableau, Looker, or similar.
• Experience with Python or R.
• Solid understanding of statistical analysis, forecasting, and scenario modeling.
• Experience running A/B tests and interpreting experiment results.
• Excellent problem-solving skills, attention to detail, and ability to work in a fast-paced environment.
• Strong communication skills, with the ability to explain findings to both technical and non-technical stakeholders.
• Curiosity, ownership mindset, and the discipline to maintain high-quality data work.

Nice to have:

• Experience with BigQuery, ClickHouse, or any cloud data warehouse.
• Basic Python knowledge for data cleaning or simple analysis.
• Exposure to subscription businesses or payment systems.
• Understanding of disputes, chargebacks, declines, or fraud signals.
• Familiarity with DBT or data quality frameworks.

• Monitor, analyze, and report on key billing and support performance indicators and emerging trends.
• Build and maintain data pipelines to ensure accurate, timely, and reliable data delivery.
• Apply statistical methods to project scenarios, assess “what-if” outcomes, and anticipate financial risks.
• Run A/B tests and experiments to evaluate billing and support strategies.
• Collaborate with cross-functional teams (Billing, Support, Finance, Product, Marketing) to align processes with risk-mitigation goals.
• Analyze the impact of marketing and product changes on billing outcomes, risk behavior, and customer support metrics.
• Provide actionable recommendations to improve billing performance and reduce disputes, churn, and operational inefficiencies.
• Document analyses, workflows, and data logic to ensure clarity and consistency.

Applicants must be located within approximately ± 4 hours of CET to ensure optimal collaboration and communication during working hours.