Data Analyst, Payments Platform
Current is a leading US-based fintech company dedicated to empowering individuals to achieve their financial goals. We're committed to providing innovative and accessible financial solutions, and data plays a crucial role in driving our success. We're looking for a talented and passionate Data Analyst to join our Payment and Platform team and help us leverage data to optimize our operations, enhance our products, and deliver exceptional customer experiences. ABOUT THE ROLE As a Data Analyst focusing on payments platform, you will be instrumental in analyzing transactional data across various payment rails and money movement activities. Your contributions will drive efficiency, uncover key insights, and support the launch and optimization of new products. You'll work closely with product managers, engineers, and other stakeholders to translate business questions into actionable insights. Your work will directly influence key decisions related to our core platform, banking products, features, and overall strategy of the company. RESPONSIBILITIES
- Analyze large datasets to uncover trends, patterns, and improvement opportunities related to card transaction processing, ACH, and other money movement activities.
- Build and maintain dashboards and reports to track KPIs and deliver clear insights to stakeholders.
- Ensure accuracy, integrity, and monitoring of transactional data across the lifecycle, supporting incident investigations and anomaly detection.
- Conduct discovery and deep-dive analyses to support data-driven decision-making.
- Partner with product managers and engineers to enable experimentation, define success metrics, feature rollouts, and measure performance.
- Drive and support strategic initiatives such as new card program setups, ACH modernization, and bank/platform migrations.
- Deliver actionable insights to leadership on emerging trends and innovation opportunities.
- Perform ledger and ACH reconciliations, identify discrepancies, and support fund settlement processes across internal and partner systems.
- Conduct opportunity sizing analyses, develop forecasting models, and present data-driven insights to influence strategic decision-making.
- Collaborate with analytics and backend engineers to maintain data integrity, accuracy, and governance throughout analytics pipelines, ensuring data is accessible, accurate, and of high quality.
- Support production analytics, incidents and fraud response through participation in on-call rotations.
This role has a base salary range of $130,000 - $175,000. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits. REQUIREMENTS
- Bachelor's degree in a quantitative field such as Analytics, Statistics, Economics, Computer Science, or a related field.
- Experience as a data analyst for 3+ years, ideally in B2C, financial services, or technology.
- Strong proficiency in SQL and experience working with MPP databases (e.g., Bigquery, Snowflake, Redshift, etc).
- Proficient in utilizing data visualization tools like Tableau, Looker, or other similar platforms.
- Excellent analytical and problem-solving skills with a strong attention to detail.
- Ability to communicate complex data insights clearly and effectively to both technical and non-technical audiences.
- Strong business acumen and the ability to translate business questions into data analysis plans.
- Experience with A/B testing and experimental design.
- Working experience with SQL and Python for data analysis.
ADDITIONAL DESIRED SKILLS AND QUALIFICATIONS
- Familiarity with the fintech industry and banking or payments domain is a plus.
- Experience with NoSQL databases such as MongoDB is a plus.
- Ability to thrive in a fast-paced, collaborative environment.
- Exposure to dimensional modeling concepts to power meaningful analytics.
- Experience building data pipelines using dbt.
- Familiarity with machine learning techniques and predictive analytics is a plus.
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