Tech Lead - Data Scientist
AI summary of the role
Lead a team of 3-6 engineers and data scientists to build and scale Obsidian's core ontology for SaaS security, covering identity, authentication, authorization, network, and data security across enterprise platforms like GitHub, Salesforce, and Workday.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Drive development of Obsidian's core ontology for unified security config analysis, AI security, and threat detection.
- Scale the ontology to cover hundreds or thousands more enterprise application platforms.
- Drive automation of repeatable R&D subtasks.
- Become an expert on foundational identity, authentication, authorization, network, and data security concepts.
What you’ll bring
- 6+ years in data science, machine learning, or applied research, with 2+ years in a technical leadership role.
- Track record of shipping production ML or data systems at scale, ideally involving ontologies, knowledge graphs, entity resolution, or semantics.
- Expert-level proficiency in Python and modern ML/data tooling.
- Experience formulating fuzzy business or security problems as concrete ML/data problems.
Technologies
Python · ontologies · knowledge graphs · entity resolution · semantics · ML · data science · SaaS security · identity · authentication
About Obsidian Security
Obsidian secures SaaS apps (Microsoft 365, Salesforce, hundreds more) by reducing posture risk, detecting threats and preventing breaches, increasingly focused on shadow AI and AI-agent access.
Series C · 200–500 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
AI tools gain privileged access to sensitive data through integrations, creating new risks most security tools miss. Obsidian uniquely detects anomalous OAuth token activity and manages integration risks. Major announcements are on the horizon. Recognizing that SaaS security needs to evolve, Obsidian enables growing organizations to start with a lightweight, prevention-focused browser extension and expand coverage over time. With global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise ahead, Obsidian is scaling rapidly toward long-term growth and IPO readiness. Tech Lead – Data Scientist About the Role We are looking for a Technical Lead to drive the development of Obsidian's core ontology that powers our groundbreaking unified security config analysis, AI security, and threat detection product. Scale this ontology as
More from the job description
Obsidian Security is the leading SaaS security platform, trusted by global enterprises like Snowflake, T-Mobile, and Algolia. We protect 200+ organizations across North America, Europe, the Middle East, Southeast Asia, Australia, and New Zealand, including many of the world’s largest Fortune 1000 and Global 2000 companies. Founded in 2017 and backed by top investors like Greylock, Obsidian was built to close a critical gap: securing SaaS apps where business happens—Microsoft 365, Salesforce, and hundreds more. The company does this by offering a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Obsidian was built by leaders who redefined endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black. Now, they’re transforming how SaaS is secured. With AI driving rapid SaaS growth and complexity, agentic AI tools gain privileged access to sensitive data through integrations, creating new risks most security tools miss. Obsidian uniquely detects anomalous OAuth token activity and manages integration risks. Major announcements are on the horizon. Recognizing that SaaS security needs to evolve, Obsidian enables growing organizations to start with a lightweight, prevention-focused browser extension and expand coverage over time. With global momentum, a growing partner ecosystem including SentinelOne, [... source excerpt omitted ...] althy dose of curiosity about the design and administration — technology, people, and process — of complex application platforms such as GitHub, Salesforce, and Workday is a must. You will love exploring rabbit holes into esoteric domain knowledge related to these topics. Formulate security problems as data and ML problems, constantly addressing and refining the customer outcome in collaboration with top-flight security teams from Global 1000 companies. What We’re Looking For 6+ years of experience in data science, machine learning, or applied research, preferably with 2+ years in a technical leadership role. A track record of shipping production ML or data systems at scale —
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