Data Science Manager, Payment Performance & Insights

The Opportunity

You will serve as the technical anchor for the newly created Payment Performance Insights team. Working directly with the VP and other payment leaders, you will be the bridge between complex, raw transactional data and strategic executive decisions.

This is a "full-stack" analytical role. You are someone who is equally at ease writing highly optimized SQL and dbt pipelines to transform raw datasets, configuring LookML backends to empower self-serve reporting, and designing rigorous statistical frameworks for pricing, product, and monetization experiments. You will have a massive influence on unlocking the power of our data and accelerating decision velocity.

What you ll do

Data Foundations, Modeling Dashboards

• Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores etc.) that enable data driven decision making.
• Partner with Flywire s centralized Data Analytics team to build our core payment data assets and to consolidate sources of truth and eliminate fragmented business logic.
• You will design the semantic layer so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards and models.
• Leverage Gen AI and modern analytics tooling to accelerate data discovery, automate documentation, and optimize pipeline maintenance.

Experimentation Testing

• Define and own Flywire s core payment experimentation methodology, setting standards for sample sizing, statistical power, and significance.
• Partner with the Monetization and Experience Product teams to design, implement, and interpret A/B tests on pricing, FX rates, and payer behavior.
• Apply advanced statistical techniques to extract the signal from noise in data that can often be highly skewed.

Anomaly Detection First Line of Defense

• Develop alerting models to spot anomalies in FX rates, margin shifts, volume mix shifts, card authorization rates, and cost structures.
• Build AI-powered automated early warning systems that monitor transactional health across thousands of corridors, scaling our defense systems far beyond manual analysis.

Strategic Analysis Insights

• Partner closely with product, engineering, and business to deeply understand their challenges and translate ambiguous business questions into actionable insights.
• Link user conversion and drop-off patterns in the payment flow to actual margin impacts that direct product improvement priorities.
• Bring proactive and influential product leadership into areas where data-driven decisions and insights are essential for success. Qualifications

Heres what we are looking for:

• Education: Bachelors degree in Statistics, Mathematics, Data Science, Economics, Computer Science, or a related quantitative field.
• Experience: 6+ years of experience applying advanced analytical methods to large-scale data, preferably within a fast-paced fintech or tech environment
• Data Modeling Core Tools: Advanced proficiency in SQL (specifically GoogleSQL/BigQuery) and Python. Proven experience developing and maintaining production-level data transformation pipelines using dbt (Data Build Tool) and building/maintaining backend semantic models in LookML (Looker)
• Statistical Rigor: Solid practical understanding of statistics, hypothesis testing, A/B test design, and experimental methodologies.
• Business Acumen: Exceptional business acumen and product sense, with a proven ability to translate strategic questions into analytical frameworks and recommendations.
• Collaboration Mindset: Excited to be a technical thought partner within a lean team while serving as a strategic thought partner to payment s leadership.

Preferred Qualifications:

• Direct domain experience in Fintech especially global digital payment, merchant acquiring, card schemes or multi-currency FX platforms.
• Deep familiarity with the Google Cloud Platform (GCP) data ecosystem (BigQuery, Looker, Vertex AI/GCP GenAI tooling).
• Experience applying advanced statistical techniques (e.g., causal inference, propensity score matching) to highly skewed transactional datasets.
• Experience using Generative AI tools to accelerate coding workflows, data exploration and predictive models.