Tech Lead - Data Scientist

Obsidian Security

Newport Beach (CA)

On-site

USD 220,000 - 250,000

Full time

14 days+
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Benefits offered by this job

Competitive compensation with equity
Comprehensive healthcare
Flexible paid time off
12 weeks of new parent leave
Professional development resources

Job summary

Obsidian Security is seeking a Technical Lead – Data Scientist in Newport Beach, CA to drive the development of their security products. The ideal candidate will have over 6 years of experience in data science or machine learning, with a proven ability to lead technical efforts. Responsibilities include scaling a core ontology and collaborating with top security teams to enhance customer outcomes. Obsidian offers competitive compensation, equity, and comprehensive benefits including healthcare and flexible time off.

Qualifications

  • 6+ years of experience in data science or machine learning, with 2+ years in a leadership role.
  • Experience shipping production ML or data systems at scale.
  • Ability to formulate complex business or security problems as ML/data problems.

Responsibilities

  • Drive the development of Obsidian's security config analysis product.
  • Scale ontology with a team of engineers and data scientists.
  • Engage with top-flight security teams for customer outcomes.

Skills

Python
Machine Learning
Data Science
Security Domains

Tools

ML/Data Tooling
Data Analysis

Job description

Founded in 2017, Obsidian Security was created to close a critical gap: securing the SaaS applications where modern business happens—platforms like Microsoft 365, Salesforce, and hundreds more.

Backed by top investors including Greylock, Norwest Venture Partners, and IVP, we’ve built a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Our team includes leaders who helped define the categories of endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black.

Now, we’re transforming how SaaS is secured—in the era of agentic AI.

Today, Obsidian is trusted by global enterprises like Snowflake, T‑Mobile, and Pure Storage. We protect more than 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.

With strong global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise on the horizon, we’re scaling quickly toward long‑term growth and IPO readiness. Join us as we define the future of SaaS security!

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 part of a team of 3-6 software engineers and data scientists 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. An unhealthy 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 — ideally systems involving ontologies, knowledge graphs, entity resolution, or semantics over heterogeneous data sources.
  • Expert‑level proficiency in Python and modern ML/data tooling.
  • Working knowledge of core security domains, or a strong ability to learn.
  • Experience formulating fuzzy business or security problems as concrete ML/data problems:
    • able to decompose ambiguous, ambitious problems into well‑scoped subproblems and design experiments with statistical rigor.
    • comfortable being scrappy and diving deep into vendor documentation, APIs, and audit logs to find the necessary data sources
    • Excellent written and verbal communication skills; ability to engage credibly with technical security practitioners at large enterprises.
Employee Benefits

Our competitive benefits packages are designed to support our employees' well‑being, both at work and at home. Our US based employees enjoy:

  • Competitive compensation with equity and 401k
  • Comprehensive healthcare with dental and vision coverage
  • Flexible paid time off and paid holiday time off
  • 12 weeks of new parent or family leave
  • Personal and professional development resources

For more details on our US benefits, or for information on our international benefits, please see here.

Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location, as well as the knowledge, skills and experience of the candidate. In addition to a competitive base salary, this position is eligible for equity awards and may be eligible for sales commission or incentive compensation based on the role or function within the company.

Base Salary Range: $220,000 USD - $250,000 USD

At Obsidian, we are proud to be an equal‑opportunity employer. We value diversity and hire for talent, passion, and compassion. In compliance with federal law, all persons hired will be required to submit satisfactory proof of identity and legal authorization. If you have a need that requires accommodation, please contact accommodations@obsidiansecurity.com. Information collected and processed as part of any job applications you choose to submit is subject to Obsidian’s Applicant Privacy Policy.

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