Optimization Data Analyst

Overview As Optimization Data Analyst, you will combine data science with business storytelling to optimize payments for merchants while building scalable analytics for internal and external stakeholders. You'll split time between supporting top customers and driving automation to scale self-service analytics for Account Management.

You'll act as an SME on payment optimization and shape next-gen BI/data infrastructure. This role offers impact at scale within a collaborative, global team driving data-driven decisions. Responsibilities Collaborate with cross-functional data teams to develop scalable analytical frameworks for large datasets.

Extract, analyze, and translate data into actionable insights and recommendations. Serve as SME on payment optimization for merchants and internal stakeholders. Shape BI/data infrastructure and build self-service tools for business users.

Turn findings into concise, compelling stories and present to internal and merchant audiences. Collaborate with Account Managers and Product teams to align data best practices and priorities. Write high-performance Python/SQL queries and develop data pipelines with PySpark and other big data tools.

Design and develop LookML models and Looker dashboards, ensuring data quality and reliability. Key requirements 5+ years in Data & Analytics Advanced PySpark/Python skills Experience with descriptive and inferential statistics Data storytelling experience for executives Proficiency with data visualization tools (Looker, Tableau) Familiarity with Spark, Airflow, and Git ETL/data pipeline design and automated data validation Ability to manage multiple priorities in a fast-paced environment Excellent communication and collaboration in a global team FinTech or Payments experience a plus analytical and structured thinking strong communication collaboration across functions PySpark Python SQL

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