Since 2004, Mandiant has been a trusted partner to security-conscious organizations. Effective security is based on the right combination of expertise, intelligence, and adaptive technology, and the Mandiant Advantage SaaS platform scales decades of frontline experience and industry-leading threat intelligence to deliver a range of dynamic cyber defense solutions. Mandiant’s approach helps organizations develop more effective and efficient cyber security programs and instills confidence in their readiness to defend against and respond to cyber threats.
The Data Science team develops innovative, data-driven solutions to today’s most challenging cybersecurity problems. By leveraging data derived from our company’s unparalleled view of the threat landscape, the Data Science team provides solutions with significant impact for our customers and the broader cybersecurity industry.
We are looking for a highly-motivated Data Scientist to help us solve these problems by applying their expert knowledge of machine learning and statistics. An ideal candidate will have previous exposure in applying machine learning and statistical techniques to cybersecurity problems, have first-hand experience building models and analytic products that have been deployed to customers. In this role, you will partner with Mandiant subject matter experts on the front lines defending against advanced threat actors, iteratively develop new capabilities, and work closely with our engineering team to deploy and maintain them. We encourage sharing the knowledge we gain through publications at academic conferences and talks at industry venues.
What you will do:
- Lead the research and development of new models and analytic products
- Explore promising areas of future research at the intersection of cybersecurity and machine learning
- Identify data sources; iterate and grow datasets over time
- Explore and analyze data; perform ad-hoc analyses to answer targeted questions
- Partner with subject matter experts to inject their in-depth knowledge into the model creation process
- Iteratively develop models and analytics; move from proof of concept to minimum viable product quickly and efficiently
- Work closely with the engineering team to develop scalable data pipelines, deploy models/analytics, and enact telemetry-driven model improvements over time
- Effectively communicate research results to stakeholders and the research community through documentation, white papers, peer-reviewed publications, and presentations
- MS/PhD in Computer Science or a related technical field is required.
- Minimum of 5+ years of experience developing and deploying machine learning models in production settings
- Minimum of 3 years experience working on cybersecurity problems, including threat intelligence, network security, endpoint security, and/or cloud security technologies.
- Experience applying a variety of unsupervised, semi-supervised, and supervised machine learning techniques, and the ability to turn big data into actionable intelligence
- Ability to analyze, retrain, and improve machine learning models
- Appreciation for the challenges in applying machine learning in a non-stationary and adversarial environment
- Significant development experience in Python
- Ability to document and explain technical details clearly and concisely (peer-reviewed publications or presentations preferred)
- Ability to provide and receive scientific critiques and work towards data-driven solutions
- Experience with scikit-learn, pandas, numpy, or similar packages
- Experience with deep learning packages, including Tensorflow, PyTorch, or Keras
- Practical background with modern ML and NLP approaches, including transfer learning, attention mechanisms, large language models, and embedding methods.
- Familiarity with cybersecurity concepts and a desire to learn from subject matter experts in the cybersecurity and threat intelligence space