Senior Data Scientist

TENEX.AI • San Jose, CA

7d • Onsite

About The Position

TENEX is seeking a Senior Data Scientist to design, build, and deploy machine learning models for its AI-driven cybersecurity platform. The role owns the end-to-end model lifecycle, from ideation and research through production deployment, monitoring, and continuous improvement. Models will support threat detection, anomaly scoring, behavioral analytics, automated alert triage, and predictive security intelligence using large volumes of cybersecurity and operational data.

The Senior Data Scientist will work with Security Operations, Product, and Data Engineering teams to turn security challenges into scalable data science solutions that contribute to client security outcomes. The work combines analytical rigor with practical engineering, including feature engineering, model evaluation, MLOps, data pipelines, and applications involving vector databases and retrieval-augmented generation (RAG).

This is an in-person opportunity based in TENEX’s San Jose, California office, with an expectation to work from the office four days per week.

Requirements

• At least 5 years of professional experience in Data Science, Machine Learning Engineering, or a related quantitative field.
• Strong theoretical and practical experience with machine learning models, including classification, clustering, time-series, and deep learning.
• Proficiency in Python and data science libraries such as Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow.
• Expertise in SQL and experience with large-scale data warehouses such as Snowflake, BigQuery, or Redshift.
• Demonstrated experience with MLOps principles, tools, and platforms, such as Kubeflow, MLflow, and Airflow or Dagster.
• Solid understanding of probability, statistics, and experimental design.
• Experience deploying and maintaining models in a cloud environment such as GCP or AWS.
• Excellent communication skills and the ability to drive projects autonomously and translate business needs into technical requirements.

Nice To Haves

• Prior experience applying data science or machine learning in cybersecurity or security analytics, particularly in MDR or MSSP environments.
• Experience with real-time or streaming data systems such as Kafka, Pub/Sub, or Kinesis for low-latency threat detection.
• Familiarity with vector databases and RAG architectures.
• Experience with modern analytics engineering frameworks.
• Experience working in an early-stage startup environment.
• A Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field, or equivalent experience.
• Relevant certifications in Data Science or cloud ML platforms.

Responsibilities

• Design, develop, train, and deploy machine learning models for threat detection, anomaly scoring, and behavioral analytics.
• Conduct feature engineering and selection on high-volume security data, including logs, network telemetry, and endpoint data.
• Own model versioning, testing, deployment, monitoring, and continuous improvement using MLOps practices.
• Research developments in data science, deep learning, and security-focused AI to drive platform innovation.
• Explore statistical methods and machine learning techniques to address emerging cyber threats.
• Design and implement A/B testing and evaluation frameworks to measure deployed model performance and impact.
• Partner with Data Engineers to define, preprocess, and structure datasets for model training and inference.
• Implement and manage data pipelines for feature extraction and model serving.
• Use vector databases and RAG pipelines for security context and large language model applications.
• Work with Security Operations to understand threats and ensure model outputs are actionable and integrated into workflows.
• Collaborate with Product Managers to define AI features and connect model performance to measurable business value.
• Present analytical findings and model behavior to technical and non-technical audiences.

Benefits

• Competitive salary and benefits package.
• Opportunities for growth and development, including expanding knowledge in AI, cybersecurity, and emerging technologies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior