TL;DR

Principal Product Analyst (Business Analytics): Lead the development of product analytics foundations, measurement frameworks, and reporting infrastructure to empower data-driven decision-making across product teams with an accent on scalable data architecture, experimentation, and cross-functional collaboration. Focus on designing and implementing analytics strategies, driving adoption of tools, and enabling strategic product decisions at scale.

Location: Remote, United States

Salary: $145,000—$232,000 USD

Company

%hirify_global% creates technology to help restaurants and local businesses succeed in a digital world by enabling business operations, sales growth, customer engagement, and employee satisfaction.

What you will do

Define and implement measurement framework strategy aligned with Product, Engineering, and Design leadership.
Lead organization-wide adoption of reporting tools, dashboards, and analytics into product development lifecycle and executive processes.
Identify gaps and recommend improvements to analytics infrastructure and tooling.
Develop standards for product data modeling, experimentation, and dashboarding.
Partner with Product teams to architect telemetry, data capture, and data science models using best-in-class reporting and AI tools.
Collaborate cross-functionally with Engineering, Data Engineering, Business Intelligence, and Data Platform teams.

Requirements

Must be based in the United States or able to work remotely within the US.
Bachelor's degree with 12+ years experience or advanced degree with equivalent experience in Product Analytics, Data Analysis, or Data Science.
Proven leadership in data/reporting implementation, tool adoption, and stakeholder training.
Strong skills in SQL, Python, R, statistical modeling, and A/B testing methodologies.
Experience with data infrastructure, schema design, and ETL/data pipelining.
Excellent communication and storytelling skills to translate complex data into actionable insights.

Nice to have

Experience with AI tooling and product data science roadmaps.

Culture & Benefits

Hybrid work model fostering in-person collaboration and individual flexibility.
Competitive compensation including base salary, bonuses, benefits, and equity.
Commitment to diversity, equity, and inclusion.
Supportive learning culture with AI tools adoption across disciplines.
Accessible and inclusive hiring process with accommodations for disabilities.