Senior Product Data Analyst

Description

VAST Data is looking for a Senior Product Data Analyst to join our growing team!

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.

"VAST's data management vision is the future of the market." - Forbes

VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.

Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company's growth and at a pivotal point in computing history.

Overview:

VAST is seeking a Senior Product Data Analyst to join our growing analytics team. The analyst will provide strategic recommendations (not just data findings) that directly influence business decisions and company strategy. The role will partner closely with business stakeholders across business functions (Engineering, Finance, Customer Success, Product Management) to uncover insights about VAST AI Operating System product usage and customer behavior and then translate those insights and actionable recommendations that drive measurable impact.

With a focus on product usage analytics of the VAST AI Operating System, the ideal candidate has a deep understanding of subscription lifecycle and specific metrics that drive SaaS growth. The analyst will define, influence, and maintain core product KPIs that inform feature adoption, user engagement, retention, and business value. This role will collaborate with stakeholders in R&D, Finance, and Customer Success to build analytics that inform decision making, increase return on investment, and improve business outcomes. The Senior Product Data Analyst will manage multiple stakeholders and present to executive and non-technical leaders.

As a Senior Product Data Analyst, this position will play a key role in transforming SaaS product usage data into analytics that inform product roadmap, enable customer success, and drive lifetime value. The analyst will lead large, complex analytics and reporting projects, delivering accurate, accessible, and repeatable business reporting linked to strategic business outcomes for the VAST AI Operating System. The Analyst will also support business partners in product management with cloud cost modeling and TCO analysis.

The role will be responsible for both building data models behind product metrics, using SQL, and creating visually compelling dashboards in Tableau. Additional responsibilities include competitive benchmarking and service level analysis across cloud reliability, durability, availability, and performance. We are seeking an analyst that can tell stories with data and deliver actionable recommendations that our stakeholders regularly use to make change within their organizations.

Essential Duties and Responsibilities

• Strategic Leadership: Translates high-level business problems and questions into specific, measurable analytics, metrics, and visualizations
• Project Ownership: Leads analytical projects end-to-end with minimal supervision, including defining scope, methodology, execution, and delivery
• Mentorship: Provide guidance and analytical support to junior analysts. Conduct peer review of code, analysis, and reports to ensure accuracy and quality
• Data Extraction: Applies advanced SQL skills to extract and transform data, ensuring data integrity and accuracy for reporting and analysis purposes
• Strategic Analysis: Design, implement, and maintain metrics, moving beyond basic reporting to establish predictive performance indicators
• Data Visualization: Design, build, and maintain high-impact Tableau dashboards that provide real-time visibility into user behavior and product adoption
• Data Management: Collaborate with engineers to validate data pipelines, understand model outputs, and improve data integrity
• Stakeholder Management: Act as a primary liaison between the analytics team and business function for all requests related to product data and analytics

Requirements

• Education: Masters degree in Business, Business Analytics Operations Management, Computer Science, Data Science or a related field preferred
• Experience: 5+ years of experience as a Data Analyst with at least 2 years focused specifically on SaaS product analytics. Familiarity with SaaS financial metrics
• Programming Languages: Proven expertise in advanced SQL for data extraction and manipulation is required. Experience with Python is a plus
• Visualization Tools: Expert in Tableau for dashboard creation, data visualization, and data storytelling is required
• Analytical Skills: Proven analytical, problem-solving, and critical thinking skills
• Domain Expertise: Knowledge with SaaS product (cloud) data sources and processes required
• Travel: Minimal travel required (approximately 10% or less annually)

Qualifications

• A relentless drive and a customer-first mentality are essential.
• An attention to detail that ensures accuracy and reliability in findings that leads to trust and credibility with stakeholders.
• The ability to break down complex problems, identify patterns, and derive meaningful insights from data.
• Intellectual curiosity with a natural desire to explore data and ask questions that lead to deeper insights.
• The ability to convey complex data insights clearly and effectively to both technical and non-technical stakeholders.
• Ability to manage multiple projects and deadlines with prioritizing tasks.
• Ability to thrive in a culture of transparency and direct feedback.