Senior Product Data Analyst

Title: Senior Product Data Analyst 

Location: United States; East Coast  

Experience: Senior Level

Job Function: Business Transformation

Employment Type: Full Time 

Industry: Computer and Network Security 

About Keyfactor 

Our mission is to build a connected society, rooted in trust, with identity-first security for every machine and human. Keyfactor helps organizations move fast to establish digital trust at scale — and then maintain it. With decades of cybersecurity experience, Keyfactor is trusted by more than 1,500 companies across the globe. We are proud to continually earn recognition as a Best Place to Work, and we achieve that through our amazing people who cultivate our culture as we grow. We hope you will trust your future with Keyfactor! 

About the position  

The Product Data Analyst role will report directly to the VP of Product Operations and work cross-functionally to analyze product usage & behavior data as well as customer outcome data. This data will help Keyfactor make decisions that influence product value/features, customer support and Keyfactor’s operational efficiency. This role will work in collaboration with other departments and leadership to guide the business with valuable information to make strategic business and roadmap decisions.  

Your efforts will help the R&D and Support teams prioritize, understand the impact, and identify areas of improvement and opportunity. Additionally, you will work with Product Managers and Engineering Managers to maintain definitions of product data & product events.  

You will have the tools in our data tech stack at your disposal and influence on future needs. You will be integral in supporting a foundation and structure in which Keyfactor can continue to scale and provide value to our customers. This includes varying levels of scope from architecture, access and optimization.  

The position is based in the United States and can be performed remotely. Applicants must hold US citizen or US permanent resident status.  

Responsibilities 

• Proactively seek out trends and create analysis frameworks to effectively answer strategic questions and translate between raw data insights and business strategy. 

• Be a driving influencer and teacher on the use and application of data and analysis. 

• Build data models in a structured data warehouse. 

• Develop reports, dashboards, and metrics to address business needs in partnership with RevOps and Customer Teams. . 

• Form opinions on tools, products, and processes we should adopt to accomplish analytics needs. 

• Form opinions on customer needs & product priorities to improve our product. 

• Partner with product, engineering, and GTM teams to ensure that we are tracking the right data to fully measure product success. 

• Optimize how teams leverage data to make roadmap decisions and prioritizations. 

• Support R&D leadership with developing and leveraging dashboards that highlight engineering and development efficiency and efficacy.  

• Establish a repeatable executive reporting cadence on product insights and suggested actions.  

• Share deep analysis conclusions and sophisticated technical methods in a clear manner to both technical and non-technical audiences to aid in adoption and engagement. 
• Lead a cross-functional data infrastructure steering committee. 

Skills and Qualifications 

• Strong analytical, communication, and project management skills. 

• Experiences with product monetization and FP&A practices.   

• Practical experience in a business environment influencing decision making with data. 

• Experience owning cross-functional support of a Business Intelligence tool. 

• Experience using SQL to transform and analyze data. 

• Experience using advanced SQL techniques (window functions, JSON flattening and extraction, etc.) for data investigation, transformation, and analysis. 

• Experience with Customer Data Platforms. 

• Experience working with R&D, business, and operations teams in an analytics capacity, especially with SaaS product analytics like trend analysis, cohort analysis, time to value, customer journeys, etc. 
• Basic understanding of prediction and personalization algorithms (e.g. purchase and churn propensity models, product recommendations). 
• Familiarity with data schemas and a solid understanding of data modeling for data warehouses. 

• The ability to effectively collaborate cross-functionally to drive actionable and measurable results. 

• A passion for the role of data in helping solve complex questions, teaching others how to use data to make decisions, and a desire to constantly learn and improve themselves. 
• Experience presenting analyses to key stakeholders at different organizational levels from IC to executive leadership.  

Please do not let doubt get in the way of you applying for this position. If you can demonstrate the abilities listed above, we want to hear from you.