26 applicants

Company

Global Payments Inc. · 3 days ago

Product Manager - Data

Nashville, TN

Full-time

Remote

Senior Level

$81K/yr - $105K/yr

6+ years exp

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Responsibilities

Define and develop the strategy for data-driven products and services, focusing on delivering actionable insights, automating processes, and enhancing decision-making for customers.

Build and maintain a product plan for data products, ensuring alignment with the overall business goals, customer needs, and market opportunities.

Continuously identify new opportunities to utilize data to improve the existing AP SaaS solution and introduce new services.

Collaborate with data engineering and data science teams to design, develop, and launch data-driven features and services such as analytics dashboards, predictive insights, benchmarking, and reporting tools.

Lead the ideation, validation, and execution of new data products, ensuring scalability, usability, and reliability.

Work with cross-functional teams (engineering, product, sales, marketing, customer success) to deliver high-quality data products that meet customer needs.

Understand customer pain points and use data to develop solutions that optimize their accounts payable processes, such as fraud detection, payment optimization, cash flow management, and supplier risk assessments.

Gather and analyze feedback from users, stakeholders, and the market to continuously improve the product and identify new areas for innovation.

Define and implement best practices for data governance, ensuring the integrity, security, and compliance of all data products, particularly with financial and regulatory standards (e.g., SOX, GDPR).

Ensure the accuracy and reliability of the data used for product development and analytics by working closely with data engineers, data analysts, and quality assurance teams.

Define key performance indicators (KPIs) for data products, tracking and analyzing product performance, usage, and customer satisfaction.

Use data to drive decision-making, identifying areas for improvement and opportunities for new product development.

Present product performance reports to stakeholders, providing actionable insights and recommendations.

Work closely with internal teams and external partners to gather data requirements, align on priorities, and ensure successful delivery of data products.

Act as the bridge between technical teams (data scientists, engineers, data analysts) and business teams (marketing, sales, customer success), translating complex data concepts into business value.

Communicate the vision, roadmap, and progress of data products clearly to leadership and other key stakeholders.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data analyticsProduct managementB2B financial operationsData analysis toolsAP processesAP SaaS platformAP solutionsAP fraud detectionPayment optimizationCash flow managementSupplier risk assessmentsData governanceData securityData complianceMachine learningPredictive analyticsAPIsData integrationCloud-based data platformsSQLSnowflakeTableauSigmaCollaboration skills

Required

Bachelor's Degree

Relevant Experience or Degree in: Business or Computer Science; Combination of relevant training and/ or experience in lieu of degree

Typically Minimum 6 Years Relevant Exp

Experience in similar business product services and/or external customer/market experience

Preferred

6+ years of product management experience, with a focus on data products, analytics platforms, or data-driven solutions.

Strong background in accounts payable, B2B payments, or financial software, with a deep understanding of AP processes and challenges.

Proven experience in using data to develop customer-centric solutions that drive business outcomes.

Bachelor’s degree in Computer Science, Data Science, Business, or a related field. Advanced degree (e.g., MBA, MS in Data Science) is a plus.

Strong proficiency with data analysis tools (e.g., Sigma, Tableau, etc.) and a solid understanding of data science concepts (e.g., machine learning, predictive analytics).

Experience working with APIs, data integration, and cloud-based data platforms (Snowflake, SQL, Striim, etc).

Excellent communication and collaboration skills, with the ability to work across both technical and non-technical teams.

Analytical mindset, with the ability to derive actionable insights from data and make data-driven product decisions.