Why This Job is Featured on The SaaS Jobs
This Senior or Staff Data Scientist role sits in a core SaaS problem space where product value, monetization, and enterprise adoption meet. The remit spans pricing and billing data, enterprise usage, and deployment health, which are foundational systems for any B2B SaaS company selling into larger customers. The cross functional interfaces with Product, Finance, Infrastructure, and Post Sales signal work that connects customer behavior to platform economics and operational readiness.
For a long term SaaS career, this kind of scope builds durable judgment around unit economics, instrumentation, and decision making under imperfect data. Experience defining trusted metrics for time to value and enterprise readiness tends to transfer across SaaS categories because it mirrors how modern subscription businesses evaluate adoption, retention risk, and expansion potential. The focus on cost optimization and scaling behavior also develops a practical understanding of how data science influences margin and reliability as usage grows.
This role is best suited to professionals who like ambiguous, end to end work and can translate between technical systems and business decisions. It will fit someone comfortable partnering across functions, owning metric definitions, and working deeply in telemetry and billing datasets where accuracy and governance matter.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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.
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