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Skills
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Authenticationunmatched
Automationunmatched
Communication Skillsunmatched
Computer Securityunmatched
Concreteunmatched
Data Scienceunmatched
Divingunmatched
Documentationunmatched
Enterprise Applicationsunmatched
Experiment Designunmatched
GitHubunmatched
Information/Data Security (InfoSec)unmatched
Machine Learningunmatched
Machine Toolunmatched
Network Securityunmatched
Ontologyunmatched
Presentation/Verbal Skillsunmatched
Problem Solving Skillsunmatched
Python Programming/Scripting Languageunmatched
Research & Development (R&D)unmatched
Salesforce.comunmatched
Security Analysisunmatched
Security Attacksunmatched
Software Engineeringunmatched
Technical Leadershipunmatched
Vendor/Supplier Evaluationunmatched
Writing Skillsunmatched
Description
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.