Remote Payments Analytics & Optimization Specialist

Pearl; United States; Remote; USD 75,000 - 110,000; Full time

Job summary

Pearl is hiring a Payments Analyst to deliver analytical support across payments performance, testing, and optimization. You will analyze payment data to identify opportunities to improve processes, raise authorization rates, and drive revenue growth.

The role emphasizes translating results into actionable recommendations and building dashboards for visibility. Join a global, data-driven team focused on enhancing customer experience and operational efficiency while exploring AI-assisted

Qualifications

• 2–4+ years of analytical experience in data-driven businesses.
• Proven track record of delivering actionable insights from data.
• Strong SQL for extracting and analyzing data from large datasets.
• Nice to have payments domain experience or familiarity with payments tech.

Responsibilities

• Conduct in-depth payment data analysis to identify patterns and opportunities.
• Identify opportunities to optimize payment processes and revenue.
• Support testing initiatives with sizing, monitoring, and readouts.
• Collaborate with cross-functional teams on payment performance projects.
• Respond to ad-hoc analyses and translate findings into actionable insights.
• Create dashboards and reporting tools for key payment metrics.
• Provide data-driven recommendations to improve authorization rates.
• Explore using AI tools to speed analysis and automate tasks.

Skills

SQL

Excel

Analytical thinking

Cross-functional

AI tools

Tools

Power BI

Tableau

Looker

Job description

Pearl is hiring a Payments Analyst to deliver analytical support across payments performance, testing, and optimization. You will analyze payment data to identify opportunities to improve processes, raise authorization rates, and drive revenue growth.

The role emphasizes translating results into actionable recommendations and building dashboards for visibility. Join a global, data-driven team focused on enhancing customer experience and operational efficiency while exploring AI-assisted