Senior Data Scientist - Payment Success

Checkout.com • Atlanta, GA

3d • Hybrid

About The Position

Checkout.com is hiring a Senior Data Scientist for its Payment Success Management (PSM) team, a merchant-facing group that diagnoses and resolves payment performance problems. The role supports US-based merchants and works alongside account managers and technical account managers. The team investigates gaps between merchant expectations and actual payment performance, including comparisons with other payment providers.

The successful candidate will own merchant performance engagements, typically lasting about three months, from kickoff and diagnosis through fixes, A/B testing, and reporting. They will analyze large, complex datasets, develop and test hypotheses, measure results, identify issues in the machine-learning optimization engine, and collaborate with ML engineering to address them. They will also present findings to merchants and non-technical stakeholders and use automation and AI to improve team efficiency.

Checkout.com describes its working model as hybrid, with three days per week in the office. The company emphasizes ownership, collaboration, accessibility, and opportunities to make an impact and grow.

Requirements

• At least 2 years of experience using data to drive measurable results, such as revenue uplift, cost reduction, or efficiency gains.
• Experience in a role with ownership of metrics and decisions.
• Strong SQL and Python skills for analysis.
• Ability to verify the accuracy of personal queries and AI-generated code.
• Ability to explain complex analysis clearly to non-technical audiences.
• Curiosity and enjoyment of solving problems without ready-made answers.

Nice To Haves

• Consulting background linking client teams and technical teams.
• Startup background with end-to-end ownership and optimization experience.

Responsibilities

• Own merchant performance engagements from kickoff through diagnosis, fixes, A/B testing, and results reporting; engagements typically last about three months.
• Analyze large, complex datasets to identify the root causes of payment performance gaps.
• Develop hypotheses, run A/B tests and other experiments, and measure performance uplift.
• Understand how the machine-learning optimization engine makes decisions, identify patterns where it makes incorrect decisions, and work with ML engineering to address them.
• Present findings and results clearly and persuasively to merchants and non-technical stakeholders.
• Use automation and AI to make the team's day-to-day work more efficient.
• Share learnings across teams.

Benefits

• Hybrid working model with flexibility and three days per week in the office.
• Accessibility accommodations can be requested for the application process or working environment.
• Opportunities for meaningful work, ownership, and professional growth.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed