Build transparency into product delivery and releases
Design and maintain reporting around product releases: scope, progress, quality signals, and post-release outcomes.
Create release-readiness and post-launch measurement frameworks (success metrics, guardrails, adoption targets).
Analyze impact of releases on customer behavior, conversion, retention, and revenue-related indicators.
Develop metrics and dashboards that reflect delivery health: throughput, cycle time, lead time, WIP, predictability, and bottlenecks.
Partner with Engineering and Product leaders to identify trends, root causes, and process improvements.
Establish operating rhythms that enable data driven decision making
Build and maintain product funnels, cohort analyses, and adoption dashboards for key workflows and features.
Identify drop-offs, friction points, and opportunities to improve activation and ongoing engagement.
Segment insights by persona, plan, channel, customer maturity, etc., to explain “what’s happening” and “why.”
Translate ambiguous questions into structured analyses and clear narratives.
Proactively surface risks/opportunities and recommend actions (not just findings).
Support roadmap decisions with evidence, tradeoffs, and forecasting where appropriate.
Work with data/engineering partners to ensure instrumentation is reliable and data definitions are consistent.
Define and document core metric definitions and build a “single source of truth” for product and delivery metrics.
Improve data quality through monitoring, anomaly detection, and governance.

Requirements

7+ years (or equivalent) in Product Analytics, Data Analytics, or a similar role supporting Product + Engineering.
Experience working in a high growth startup, managing and improving fragmented data + building scalable models
Deep experience turning product and engineering datasets into insights: releases, velocity, adoption, funnels.
Strong SQL skills and comfort working directly with event data, product telemetry, and engineering workflow data.
Proven ability to create metrics frameworks (North Star + supporting metrics) and keep definitions consistent.
Experience building dashboards and recurring reporting that executives actually use.
Proficiency with Looker, Fullstory, Jira, Launch Darkly and Snowflake.
Familiarity with Agile/modern delivery metrics and tools and concepts like cycle time, lead time, throughput, and predictability.
Ability to connect engineering activity to customer outcomes
Strong storytelling: you can explain the “so what” clearly to executives and teams.
Comfortable pushing back, asking great questions, and aligning stakeholders around what to measure and why.
High ownership: you don’t wait for requests, you proactively surface insights and recommendations.
Experience with experimentation, A/B testing, and causal inference approaches is nice to have.
Experience defining event tracking plans and working with engineers on instrumentation is nice to have.
Comfort with lightweight forecasting models and capacity/roadmap scenario analysis is nice to have.
You’ll work closely with the CPO, Product Managers, Engineering leaders, and Data/Analytics.
You’ll operate with high autonomy and will be expected to build and iterate quickly balancing speed with accuracy and trust.

Benefits

Competitive salary
Equity
Unlimited PTO and paid holidays
Remote-first with offices in New York City and San Francisco
Health benefits, including medical, dental, vision, mental health support, parental leave, life and AD&D insurance, and disability
401(k)
Work-from-home and commuter benefits
Laundry allowance to support our customers’ businesses
Comprehensive training, learning, and development programming
Access to hundreds of discounts and rewards from renowned vendors, including deals on health & wellness, travel, dining, auto insurance, and so much more!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLproduct analyticsdata analyticsmetrics frameworksdashboard creationevent trackingA/B testingcausal inferencedata quality monitoringdata governance

Soft Skills

storytellingstakeholder alignmentproactive insight generationquestioninghigh ownershipdata-driven decision makinganalytical thinkingcommunicationcollaborationproblem-solving