Senior Data Scientist- Cybersecurity
About this role
The Static AI team at SentinelOne builds advanced machine learning models that operate on millions of machines worldwide, evaluate billions of events daily, and make sub-second decisions to stop malware before execution. This senior team member researches, develops, ships, and supports malware detection engines across Windows, Mac, Linux, and cloud environments by blending data science, machine learning engineering, and software engineering capabilities.
Prague-based or remote practitioners in the Czech Republic and Slovakia will own projects end-to-end, translating complex security requirements into scalable production systems. A successful candidate brings deep technical independence, a collaborative mindset suited for a globally distributed group, and practical experience training classical machine learning algorithms on large datasets. The role suits pragmatic engineers who enjoy solving difficult problems where traditional machine learning meets the unique constraints of real-time cybersecurity.
What you will do
- Design and deliver innovative machine learning detection engines capable of making sub-second decisions to prevent malware execution.
- Research emerging artificial intelligence approaches and collaborate with peers to integrate promising advancements into the product.
- Build robust analytics systems that ingest internal and external data sources to enhance existing models and formulate new ones.
- Collect, curate, and tailor large datasets specifically for training machine learning models.
- Manage projects end-to-end from initial research through production deployment while navigating complex operational settings.
- Communicate technical solutions effectively with cross-functional partners across product, support, and engineering departments.
What you need
- Hold a degree in Computer Science, Mathematics, or possess equivalent practical experience.
- Demonstrate at least 3 years of professional background designing, training, and evaluating machine learning models in production environments.
- Bring solid grounding in fundamental machine learning concepts and statistics, alongside expertise with classical machine learning algorithms.
- Actively incorporate artificial intelligence tools into your daily professional workflow.
- Exhibit strong independent problem-solving abilities to handle inconvenient and challenging technical settings without constant oversight.
- Communicate clearly and collaborate smoothly within a diverse, globally distributed team.
Nice to have
- Cyber domain experience working on security products, particularly detection systems and static file analysis
- Cloud infrastructure and MLOps experience
- Experience with Spark, PySpark, or Databricks
Benefits
- Restricted Stock Units (RSUs) and Employee Stock Purchase Plan (ESPP)
- Performance-based bonus
- Flexible time off on top of standard 5 weeks PTO, paid company wellness days, and fully paid short-term sick or nursing leave
- Private medical care, life and disability insurance, pension insurance contribution, and global business travel medical insurance
- Global home office allowance, meal allowance, wellbeing allowance, MultiSport benefit program, and Wellness Coach app access
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
The position offers hybrid work options in Prague (Karlin) and Brno (Clubco), or remote flexibility within the Czech Republic and Slovakia. Only Prague-based employees are required to work from the office at least 2 days per week.
What specific machine learning experience is required?
Candidates must have 3 or more years of experience designing, training, and evaluating machine learning models in production systems. This includes expertise in collecting and tailoring large datasets for classical machine learning algorithms alongside fundamental statistics.
What team will I be joining and what do they build?
You will join the Static AI team, which builds state-of-the-art machine learning models operating on millions of machines worldwide. The team evaluates billions of events daily to make sub-second decisions that stop malware before it runs.
Are there any preferred technical backgrounds for this position?
Cyber domain experience working on security products, particularly detection systems and static file analysis, is preferred. Additionally, cloud infrastructure, MLOps, Spark, PySpark, and Databricks experience are considered strong pluses.