Come join the company building the security operating model for the age of AI. AI has changed how data is used – and security must change with it. our company's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI – from data to access to model. Instead of perimeter controls and static policies, our company provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the worlds leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security.
About the Team
This team builds the core scanning logic that allows our company to operate at true enterprise scale. Its mission is to expand data coverage and increase scanning efficiency by designing intelligent processing strategies, heuristics, and models tailored to different data types and environments. By making scanning faster, more scalable, and more cost-effective, the team enables our company to analyze vastly more data across customer estates-turning large-scale classification from a theoretical capability into a practical, affordable reality for organizations of any size.
What Youll Do
Lead applied research to improve large-scale data scanning, from hypothesis formulation to validation and impact measurement.
Investigate system and data behavior at scale to surface constraints and opportunities for smarter scanning.
Design heuristics and processing logic that scale the product while keeping classification quality as a north star.
Translate research findings into scalable, production-ready solutions under real system constraints.
Collaborate closely with data science, engineering, and product teams to influence product decisions through data-driven insights.
About the Team
This team builds the core scanning logic that allows our company to operate at true enterprise scale. Its mission is to expand data coverage and increase scanning efficiency by designing intelligent processing strategies, heuristics, and models tailored to different data types and environments. By making scanning faster, more scalable, and more cost-effective, the team enables our company to analyze vastly more data across customer estates-turning large-scale classification from a theoretical capability into a practical, affordable reality for organizations of any size.
What Youll Do
Lead applied research to improve large-scale data scanning, from hypothesis formulation to validation and impact measurement.
Investigate system and data behavior at scale to surface constraints and opportunities for smarter scanning.
Design heuristics and processing logic that scale the product while keeping classification quality as a north star.
Translate research findings into scalable, production-ready solutions under real system constraints.
Collaborate closely with data science, engineering, and product teams to influence product decisions through data-driven insights.
Requirements:
Must-Haves
Bachelor's or Master's degree in a field related to data science, such as computer science, statistics, or mathematics, or equivalent experience.
5+ years of experience as a Data Scientist/Applied AI Researcher/Algorithm Researcher or equivalent hands-on experience in research and analysis of large datasets.
Proficiency in Python, and experience with data science libraries and frameworks.
Strong understanding of database management and SQL.
Excellent analytical, problem-solving, and critical thinking skills.
Highly motivated, self-driven, and independent.
Experience working on core, production-facing components of a SaaS product.
Experience with LLMs and prompt engineering – advantage.
Must-Haves
Bachelor's or Master's degree in a field related to data science, such as computer science, statistics, or mathematics, or equivalent experience.
5+ years of experience as a Data Scientist/Applied AI Researcher/Algorithm Researcher or equivalent hands-on experience in research and analysis of large datasets.
Proficiency in Python, and experience with data science libraries and frameworks.
Strong understanding of database management and SQL.
Excellent analytical, problem-solving, and critical thinking skills.
Highly motivated, self-driven, and independent.
Experience working on core, production-facing components of a SaaS product.
Experience with LLMs and prompt engineering – advantage.
This position is open to all candidates.
