Requirements

• Bachelor’s degree in a quantitative field (Data Science, Computer Science, Statistics, Finance, Engineering, etc.)

• Strong technical skills in SQL, Python (Pandas), and Excel

• Experience working with large datasets, data reconciliation, or anomaly detection

• 2+ years’ experience in data analytics, revenue assurance, or a related role

• Experience in telecom, subscription businesses, or fintech is a plus

Key strengths:

• Strong analytical thinking and attention to detail

• Problem-solving mindset with the ability to investigate data variances

• Ability to translate data into actionable business insights

• Execute and maintain revenue assurance controls across sales, provisioning, billing, payments, and inventory systems

• Perform key reconciliations (Billing vs Provisioning, Sales vs Installation vs Billing, Payments, Inventory) to identify inconsistencies and leakages

• Develop and optimize SQL queries and Python scripts to automate recurring checks and improve efficiency

• Analyze large datasets to detect anomalies, quantify revenue impact, and support root cause investigations

• Build automated reports and dashboards to monitor key revenue assurance metrics

• Drive process improvements and reduce manual effort through automation