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We are seeking a Billing Data Analyst to join our Billing and Data team. You will play a key role in analyzing financial performance, billing behavior, risk trends, and support operations. Your work will help drive better decision-making, reduce financial risks, and improve billing efficiency across all products. This role combines analytical rigor, statistical thinking, and cross-functional collaboration.
Job Responsibility:
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
Requirements:
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