United States
Remote
Senior
Full Time
23 days ago
💰$115,600 - $153,170
remoteB2B SaaSdata analysisproduct analyticsSQLLookerMixpanelMetabaseSegmentA/B testing
Requirements
- •5+ years of experience in data analysis, business intelligence, or a related quantitative field.
- •Demonstrated experience in product analytics for a B2B SaaS product, including funnel analysis, retention modeling, cohort analysis, and feature adoption metrics.
- •Strong proficiency in SQL, including both ad-hoc querying and data modeling for analytical reporting, especially for event-level datasets and behavioral analytics.
- •Strong experience instrumenting and validating product usage event data, preferably using Segment or comparable customer data platforms.
- •Experience with at least one data visualization platform (Looker or Metabase preferred) with the ability to design intuitive dashboards and optimize reporting structures.
- •Ability to validate data across complex or undocumented systems, ensuring accuracy and consistency across outputs.
- •Proven ability to translate product questions into structured analytical approaches that inform feature development and product strategy.
- •Experience partnering directly with product managers, UX researchers, and engineers to define metrics, design experiments, and support product discovery.
- •Ability to communicate user behavior insights in a compelling narrative that informs product decisions for both technical and non-technical stakeholders.
What You'll Do
- •Serve as a strategic analytics partner to product managers, UX researchers, and engineers to define analytics requirements for new product features, including identifying key user behaviors and success metrics.
- •Create scalable product analytics dashboards and self-service tools tailored to product managers, UX partners, engineers, and designers, using SQL, Looker, Mixpanel, Metabase, Python, or R.
- •Partner with engineering and analytics engineering to implement and QA product event collection with Segment, ensuring events follow naming conventions, are consistently structured, and are modeled for high-quality downstream analytics; audit event coverage to identify gaps and improve the reliability of behavioral data.
- •Conduct deep-dive behavioral analyses (e.g., funnel, cohort, time-to-value, retention, feature adoption) to uncover user needs, friction points, and opportunities to improve the product experience.
- •Synthesize quantitative data with qualitative insights to inform product strategy and shape feature roadmaps.
- •Build frameworks that measure long-term product engagement, user journeys, and the impact of new features on customer outcomes.
- •Collaborate with product teams to design, instrument, and analyze A/B tests and other experimental methodologies; provide interpretation of lift, impact, and risks.
- •Support product discovery by developing hypotheses, generating exploratory analyses, and identifying emergent behavioral patterns.
- •Validate data accuracy by comparing results across source systems and performing root-cause analysis on anomalies or unexpected metric behavior.
- •Enable self-service analytics by educating stakeholders on data sources, metric definitions, and reporting tools; identify opportunities to improve clarity and usability of reporting.
- •Partner with Analytics Engineering and Data Engineering teams to define data requirements, improve data quality, and ensure reliable data pipelines and modeling layers.
- •Contribute to and uphold team best practices for data modeling, visualization standards, and documentation.
- •Participate in peer review processes for data models, dashboards, and analyses, ensuring quality, consistency, and alignment with team standards.
- •Share knowledge and emerging best practices with teammates, contributing to documentation and helping strengthen data literacy across the organization.
- •Support hiring processes for new analysts by participating in interview loops or technical assessments, as needed.
Nice to Have
- •Experience defining and maintaining a product analytics tracking plan or taxonomy.
- •Experience implementing best practices for client-side and server-side event tracking, including schema governance and QA workflows.
- •Experience using Mixpanel or a similar tool to visualize user behavior funnels and analyze product dataExperience working with product experiment platforms and A/B testing.
- •Familiarity with data engineering or analytics engineering concepts (e.g., dbt, ETL workflows, version control, data model documentation).
- •Experience with survey feedback analysis and qualitative analysis.
Benefits
- •Bonus-eligible
- •Robust suite of benefits
About Articulate
Articulate develops a workplace training platform that provides online courses for management systems.
New York, NY, US
250 - 500
Education