Empregos de escritório remoto e em casa em mountain-view ∙ Página 5
1117 Empregos à distância e em escritório em casa online
Senior Software Engineer – Quality Engineering
ID.me · Mountain View, Estados Unidos Da América · Remote
Senior Software Engineer - Developer Portal
ID.me · Mountain View, Estados Unidos Da América · Remote
Principal Tech Lead Manager - Data Platform & Reliability Engineering
ID.me · Mountain View, Estados Unidos Da América · Remote
Principal Engineer Person & Trust Platform
ID.me · Mountain View, Estados Unidos Da América · Remote
Senior Software Development Engineer - Shopping Graph
ID.me · Mountain View, Estados Unidos Da América · Remote
Staff Software Engineer - Wallet/Authentication Platform
ID.me · Mountain View, Estados Unidos Da América · Remote
Senior Software Engineer - Wallet/Authentication Platform (Client & Credentials)
ID.me · Mountain View, Estados Unidos Da América · Remote
Software Engineer III – Trust Service Team
ID.me · Mountain View, Estados Unidos Da América · Remote
Staff Software Engineer – Trust Service Team
ID.me · Mountain View, Estados Unidos Da América · Remote
Sr. Software Engineer - Wallet - Authentication
ID.me · Mountain View, Estados Unidos Da América · Remote
Senior Data Scientist, Growth
Glean · Mountain View, Canadá · Remote
- Define and evolve Glean’s growth measurement framework across acquisition, activation, engagement, retention, resurrection, and expansion. Own core metrics such as WAU, activation, engagement intensity, retention, and feature adoption.
- Build and analyze end-to-end user and account funnels to identify where users realize value, where they drop off, and which behaviors predict durable engagement.
- Identify and size high-leverage opportunities across onboarding, product discoverability, education, lifecycle messaging, collaboration and virality, and new product surfaces.
- Partner with Product, Design, and Engineering to turn product ideas into testable hypotheses, clear success metrics, instrumentation plans, and decision criteria.
- Design and analyze A/B tests, phased rollouts, and quasi-experiments. Apply causal inference to recommend whether products should launch, iterate, or change direction.
- Develop behavioral and needs-based segments and translate insights into targeted product interventions.
- Inform roadmap and investment decisions by quantifying reachable populations, expected impact, confidence, dependencies, and tradeoffs before significant development begins.
- Build trusted, reusable growth datasets, dashboards, metrics, and self-serve analytical tools so Product and Engineering can independently understand product health and investigate changes.
- Lead cross-functional data science projects end-to-end—from ambiguous product questions to clear insights, recommendations, and decisions for audiences ranging from engineers to executives.
- Example areas of focus include improving new-user onboarding and activation, converting occasional users into habitual users, increasing adoption of emerging AI experiences, optimizing high-traffic entry surfaces, improving feature discovery, developing lifecycle strategies, and building account-level adoption frameworks for enterprise customers.
- 7+ years of experience in quantitative data science, product analytics, or growth analytics, plus a degree in Statistics, Mathematics, Computer Science, or a related field.
- Strong grounding in statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis.
- Demonstrated experience designing and analyzing product experiments and translating causal findings into clear product decisions.
- Strong proficiency in SQL and practical fluency in Python or R.
- Experience building durable analytical datasets, metrics, dashboards, and data models—not relying primarily on ad hoc analysis. dbt experience is a plus.
- Demonstrated ability to partner with Product and Engineering teams to identify opportunities and influence roadmap decisions.
- Exceptionally high AI proficiency through habitual, high-value use of LLMs, with sound judgment about when and how to apply them, rigorous validation, and continuous workflow improvement.
- A strong product and business mindset, including experience defining KPIs, guardrail metrics, and measurement frameworks that influence decisions.
- Ability to independently own complex projects end-to-end, from problem framing and measurement through analysis, recommendation, and follow-through.
- Clear, concise communication skills, with the ability to explain complex quantitative findings to both technical and non-technical audiences.
- You are particularly a good fit if you:
- Have experience in B2B SaaS, especially enterprise AI, or with products adopted across both users and accounts.
- Have identified growth opportunities from behavioral data and turned them into shipped, measurable product improvements.
- Have built experimentation or product-measurement capabilities that improved the speed and quality of organizational decision-making.
- Combine quantitative rigor with strong product intuition and are comfortable making recommendations in ambiguous environments.
- Bring strong ownership and self-motivation, with a focus on business impact and continuous growth.
- Manage changing priorities while consistently delivering core initiatives.
- This role is hybrid (4 days a week in our Mountain View office)
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