Senior Data Scientist

1d1 day ago

TENEX.AI

San Jose, US · Full-time · $170,000 – $230,000

About this role

TENEX.AI is an AI-native automation-first Managed Detection and Response provider backed by Andreessen Horowitz and other leading investors. We seek a Senior Data Scientist to design, build, and deploy machine learning models powering our cybersecurity platform. This foundational role delivers high-fidelity threat detection and predictive security intelligence.

You will manage the end-to-end lifecycle of machine learning models from research to production deployment and monitoring. Leverage large volumes of cybersecurity data to create models for anomaly detection, threat scoring, and automated alert triage. Apply MLOps best practices for model versioning and continuous improvement.

Collaborate closely with Security Operations, Product, and Data Engineering teams to translate security challenges into data science solutions. This in-person role requires working from the San Jose office four days per week. Our culture emphasizes irreplaceable collaboration and community in the workplace.

Join a fast-growing startup on the ground floor with substantial recent funding. As an early employee you will help shape our culture and gain meaningful ownership over high-impact initiatives. Enjoy limited risk and unlimited upside while building the next-generation cybersecurity platform.

Requirements

Expertise in machine learning model development and deployment for security applications.
Proficiency in handling large-scale security data such as logs, network telemetry, and endpoint data.
Strong background in anomaly detection, threat scoring, and behavioral analytics.
Experience with MLOps practices including model versioning, testing, and monitoring.
Ability to work on high-velocity data streams to deliver mission-critical AI for cybersecurity.

Responsibilities

Design, develop, train, and deploy high-performance machine learning models for threat detection, anomaly scoring, and behavioral analytics.
Conduct feature engineering and selection on vast, high-velocity streams of security data including logs, network telemetry, and endpoint data.
Own the model lifecycle, including versioning, rigorous testing, and continuous improvement through MLOps best practices.
Stay up-to-date on state-of-the-art research in data science and apply innovations to cybersecurity challenges.
Translate complex security challenges into data science problems ensuring AI/ML solutions are effective and scalable.
Generate predictive security intelligence that directly contributes to clients' security outcomes.

Benefits

Opportunity to define and build company culture as an early employee.
Meaningful ownership over high-impact initiatives.
Backed by top tier investors including Andreessen Horowitz with substantial recent funding.