Data-Driven Optimization: Analyze large payment datasets to identify trends and opportunities.
Scalable Tooling & Automation: Build scalable analytics solutions and automation pipelines.
Cross-Functional Collaboration: Partner with Product, Data, and Commercial teams.
Advanced Problem-Solving & Experimentation: Lead A/B tests and data investigations.
Strategic Data Storytelling: Synthesize data into clear narratives for decision-making.
Mentorship & Best Practices: Share knowledge and elevate analytics standards.

🎯 Requirements

3–5 years in data analytics/science, fintech/payments or tech.
Strong Python, SQL, PySpark skills with large-scale data processing.
Design scalable ETL/data pipelines with data validations.
Familiar with Spark, Airflow, and Git.
Experience with Looker or Tableau for dashboards.
Solid stats knowledge: hypothesis testing and data mining.

🎁 Benefits

Office-based role; in-person collaboration; not remote-only.

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