Senior Data Product Manager

About Reap

Role Overview

What You'll Do

• Establish and enforce strong data governance policies, ensuring compliance with PII protection and data privacy standards across all data products.
• Collaborate with data engineers and analysts to design and build scalable, AI-enhanced self-service data tables that empower end users.
• Work on data pipelines by deeply understanding their integration purposes, and develop better use cases for analytical data table builds using existing data assets.
• Apply strong skills in data mapping and standardization to ensure consistent, high-quality data across platforms.
• Translate finance and operational business needs into clear product requirements for analytics, cost saving, churn prediction, and data usability.
• Lead development and deployment of data solutions supporting financial reporting, forecasting, operational efficiency, and cost reduction strategies.
• Leverage FX expertise to integrate foreign exchange data impacts into analytics and decision-making tools.
• Build and leverage AI agents to develop predictive models such as churn prediction and automate the optimization of data structures for enhanced self-service capabilities, reducing dependency on engineering resources.
• Prioritize and manage product features that deliver measurable cost savings, enhance customer retention, and improve data accessibility.
• Ensure ongoing monitoring and auditing of data quality, privacy, and compliance, especially for sensitive financial datasets.
• Use data-driven insights and product metrics to evaluate and continuously improve AI-powered data products.
  

What We’re Looking For

• You have 3+ years of experience as a data product manager or 5+ years as a data analyst.
• Strong understanding of data architecture, data pipeline design, and ETL processes.
• Proficiency in data analysis and visualization tools (e.g., SQL, Python, Tableau, Power BI).
• Experience in defining product requirements and translating business needs into technical specs for data products.
• Knowledge of AI/ML concepts and experience leveraging AI agents or automation tools to build and optimize data solutions.
• Familiarity with data governance frameworks, PII compliance, and data privacy regulations.
• Understanding of finance and operational data domains, including FX.
• Skills in data mapping, standardization, and metadata management to ensure data consistency and quality.
• Experience working with cross-functional teams, including data engineering, ML engineers, and analysts.
• Ability to prioritize features based on business impact and drive measurable cost savings or efficiency gains.
• Strong communication skills to convey technical concepts and product updates effectively to diverse stakeholders.