Senior Data Analyst

Role Overview

Senior Data Analyst focused on product analytics, behavioral analysis, and predictive analytics to drive product and business decisions with data-driven insights.

Responsibilities

• Lead analysis of user behavior and trends using advanced statistical methods and predictive models to improve engagement and retention.
• Develop and standardize product metrics aligned to company OKRs; use cohort analysis to understand user lifecycles and influence customer lifetime value (CLV).
• Design and execute experimental strategies, including A/B tests, to measure impact of product changes and inform the product roadmap.
• Create and maintain scalable reporting so key metrics are accessible across teams while ensuring data accuracy and integrity.
• Collaborate with cross-functional teams to define and capture data, translating business questions into actionable insights.
• Produce clear reports and visualizations for both technical and non-technical stakeholders.
• Manage stakeholder relationships, expectations, and delivery timelines.
• Support customer success and sales enablement with data-backed proof points for case studies and sales narratives.
• Mentor junior analysts and document/standardize best practices for analytics and reporting.

Requirements

• Bachelor’s degree in a relevant field (Data Science, Statistics, Mathematics, Computer Science or related); Master’s preferred.
• 3–5+ years hands-on experience in product and customer analytics, ideally B2B/SaaS (usage/engagement, lifecycle metrics).
• Strong proficiency in SQL and Python or R, with the ability to write efficient queries and build reproducible pipelines.
• Experience with data visualization/BI, with Tableau strongly preferred.
• Familiarity with a modern data stack, including:
  • Redshift (cloud database)
  • Airflow (ETL/pipeline orchestration)
  • Segment and/or Amplitude (product analytics)
  • GitHub and other version control/data tools
• Experience with experimental design and A/B testing.
• Ability to lead multiple initiatives: problem definition, success metrics, experiment design, and communication of results.
• Strong understanding of data governance and data quality.
• Excellent written and verbal communication; strong problem-solving and attention to detail.

Nice to Haves

• Experience in the Real Estate industry.

Location

• Murray, UT