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gleanwork
Страна
США
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175 000 $ – 250 000 $
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Senior/Staff Data Scientist, Infrastructure

Оценка ИИ

Отличная позиция в одной из самых инновационных ИИ-компаний мира с конкурентной зарплатой, сильным пакетом льгот и возможностью напрямую влиять на экономику продукта.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена требованием 7+ лет опыта, необходимостью глубокого понимания экономики облачной инфраструктуры и умением работать с 'сырыми' данными в быстрорастущем ИИ-стартапе.

Анализ зарплаты

Медиана215 000 $
Рынок180 000 $ – 260 000 $
Оценка ИИ

Предложенный диапазон $175k - $250k полностью соответствует рыночным стандартам для позиций Senior/Staff уровня в Сан-Франциско, где медиана для опытных Data Scientist в топовых стартапах составляет около $210k-220k без учета опционов.

Сопроводительное письмо

I am writing to express my strong interest in the Senior/Staff Data Scientist, Infrastructure position at Glean. With over 7 years of experience in quantitative data science and a deep background in B2B SaaS, I have consistently focused on bridging the gap between complex infrastructure telemetry and business-critical decision-making. My expertise in SQL, Python, and modern data stacks like dbt aligns perfectly with your need for a specialist who can navigate nascent datasets to drive cost optimization and enterprise readiness.

In my previous roles, I have successfully modeled unit economics for compute-intensive workflows and developed KPI frameworks that directly influenced pricing and packaging strategies. I am particularly drawn to Glean’s mission of redefining enterprise knowledge through its Enterprise Graph. I am eager to apply my skills in statistical modeling and analytics engineering to ensure Glean’s infrastructure scales sustainably while delivering measurable value to your global customer base.

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Присоединяйтесь к Glean, чтобы оптимизировать экономику ИИ-решений нового поколения и влиять на стратегию ценообразования ведущей платформы корпоративного поиска.

Описание вакансии

About Glean:

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.

At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.

Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.

If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.

About the Role:

Glean is building a world-class data organization spanning data science, applied science, data engineering, and business analytics. This role sits within the Growth and Enterprise Readiness data science team, with a primary focus on pricing, billing, and enterprise usage, alongside broader time-to-value and deployment health metrics.

In this role, you’ll work at the intersection of Product, Finance, Infrastructure, and Post-Sales to ensure Glean’s pricing and enterprise experience are grounded in clear, trusted data.

You will:

  • Become a deep expert in Glean’s product telemetry, billing data, and platform systems, partnering closely with Product, Finance, and Infrastructure to self-serve insights
  • Develop and evolve metrics that capture enterprise readiness, deployment health, and time-to-value, from initial rollout to sustained adoption
  • Drive deployment and infrastructure cost optimization by analyzing usage patterns, workload drivers, and scaling behavior across customers.
  • Partner with platform and infrastructure teams to model and optimize the economics of core systems such as connectors, indexing, and knowledge graph infrastructure, ensuring margins scale sustainably with usage growth
  • Support pricing, packaging, and monetization decisions through thoughtful analysis of usage, consumption, and cost drivers
  • Improve observability and data quality for billing and enterprise-critical workflows, identifying gaps and driving alignment across systems
  • Build analytics and models to support security and trust initiatives, including threat detection, abuse patterns, and monitoring for enterprise-critical products
  • Analyze and improve the cost efficiency of compute-intensive workflows (eg: mining and indexing), identifying trade-offs between product value, performance, and unit economics.
  • Lead cross-functional data science projects end-to-end, translating ambiguous problems into clear, actionable insights
  • You will collaborate closely with Product Management, Engineering, Finance, Billing Operations, and GTM leadership to ensure Glean’s pricing, billing, and enterprise readiness strategies are grounded in high-quality data and clear, trusted metrics.

About you:

  • 7+ years of experience in a highly quantitative data science role, with a degree in Statistics, Mathematics, Computer Science, or a related field
  • Strong proficiency in SQL and Python, and experience working with modern data stacks (e.g., dbt, analytics engineering pipelines)
  • Experience analyzing nascent, complex datasets and translating them into clear, actionable insights
  • A strong product and business mindset, with experience defining KPIs, guardrail metrics, and dashboards that influence decisions
  • Solid grounding in statistics, including experimentation and non-experimental methods
  • Ability to independently own projects end-to-end, from problem framing to delivery
  • Clear, concise communication skills, with the ability to explain complex analyses to both technical and non-technical audience
  • You have experience in B2B SaaS, especially in the enterprise AI space.
  • You have a very strong sense of ownership and self-motivation. You are laser-focused on delivering business impact while growing as an individual along with Glean.
  • You are good at managing evolving priorities while successfully delivering core initiatives.
  • You have experience working with collaborators across large time zone differences.

Location:

  • This role is hybrid (4 days a week in one of our SF Bay Area offices)

Compensation & Benefits:

The standard base salary range for this position is $175,000 - $250,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

#LI-HYBRID

AI-First Mindset at Glean:

At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.

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Навыки

  • SQL
  • Python
  • dbt
  • Statistics
  • Data Science
  • Analytics Engineering
  • SaaS
  • Unit Economics
  • Experimentation

Возможные вопросы на собеседовании

Проверка опыта в оптимизации затрат на инфраструктуру, что является ключевой частью роли.

Расскажите о случае, когда ваш анализ данных привел к значительному снижению затрат на облачную инфраструктуру или вычислительные ресурсы. Какую методологию вы использовали?

Оценка способности кандидата работать с неопределенностью и новыми данными.

Как вы подходите к созданию метрик 'здоровья внедрения' (deployment health) для нового продукта, где исторические данные ограничены или отсутствуют?

Проверка навыков статистического моделирования в контексте бизнеса.

Как бы вы оценили влияние изменения модели ценообразования (например, переход от подписки к потреблению) на отток клиентов, используя неэкспериментальные методы?

Роль требует тесного взаимодействия с инженерами и финансистами.

Опишите ваш опыт взаимодействия с командами Infrastructure и Finance. Как вы разрешаете конфликты, когда цели по производительности продукта противоречат целям по маржинальности?

Glean делает акцент на AI-грамотности.

Как вы используете современные LLM или ИИ-инструменты в своем ежедневном рабочем процессе для повышения эффективности анализа данных?

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gleanwork
Страна
США
Зарплата
175 000 $ – 250 000 $