Staff Product Analyst

Gusto is looking for highly skilled and motivated Data Analysts with extensive experience (ideally 7 years or more) applying their expertise in a business environment. As a Data Analyst, you will play a crucial role in leveraging data to drive strategic decision-making and contribute to the overall success of our organization. The ideal candidate is a skilled data storyteller with a strong analytical mindset, top-notch SQL skills, dedication to keeping data accurate and documented, an eye for data visualization design, and a passion for applying these skills to help small businesses thrive.

In this role you will work closely with our Decision Science, Business Intelligence, Finance, Product, Engineering, and other teams to become an expert in the data for your domain, define and track metrics that help us understand our business performance, and dive deep into our Payroll, Benefits, and HR data to deliver insights, answer questions, and drive impact. We have multiple senior roles open, each focused on a different area of our business.

In this role, you will be responsible for:

• Leading: Own ambiguous problems, interact with multiple stakeholders, and establish structures and processes to take our analytics to the next level.
• Data Thought Partnership: Collaborate with product managers, engineering leads, designers, and operations teams to drive data efforts for large product areas. Help identify what is working, discover growth opportunities, and evaluate data that informs key decisions.
• Data Analysis: Collect, clean, and analyze data to extract meaningful insights and identify trends, patterns, and correlations relevant to our business, products, and services.
• Reporting and Visualization: Develop and maintain dashboards, reports, and visualizations to effectively communicate key findings and trends to stakeholders.
• Data Quality: Review data integrity, accuracy, and metric logic. Identify and work with relevant teams to resolve data issues and implement data governance best practices.
• Performance Tracking: Monitor and evaluate the performance of our products and services, conducting regular data-driven reviews and providing actionable recommendations for improvement.
• Inference: Apply basic statistical techniques, like hypothesis testing, to draw meaningful insights, assess causality, and support confident decision-making.
• Influence: Work closely with members of our other Data Teams - Decision Science, Analytics Engineering, and Data Platform - to promote a data-informed mindset across the company through education and role modeling.
• Builder Mindset: Be responsive, build and iterate quickly, take ownership of the data needs and opportunities in your area, stay curious, and produce data products that help the business.

What we're looking for:

• Successful applicants typically have between 7-10 years of experience at a product-focused software company.
• Experience working with and analyzing complex datasets, including QA, querying, summarizing, visualizing, and reporting findings.
• Excellent SQL skills with demonstrated ability to write efficient queries.
• Excellent project management skills.
• Excellent communication skills, capable of effectively delivering findings and recommendations to non-technical stakeholders in a clear and compelling manner.
• Expertise in data visualization tools (e.g. Tableau, Looker, Hex, Omni, etc)
• Experience collaborating with data engineering teams to design and implement data models that facilitate data analysis, reporting, and business intelligence needs.

If you are passionate about using data to drive strategic decisions and help small businesses thrive, we'd love to hear from you!

Our cash compensation amount for this role is targeted at $112,000-$157,000/yr in Denver, Chicago, Miami, Austin and Atlanta, $122,000-$171,000/year in Los Angeles, $136,000-$190,000/yr for San Francisco, Seattle and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.