Data Scientist

_At Securonix, we’re on a mission to secure the world by staying ahead of cyber threats, reinforcing all layers of our platform with AI capabilities. Our_**_ Securonix Unified Defense SIEM_**_ provides organizations with the first and only AI-Reinforced solution built with a cybersecurity mesh architecture on a highly scalable data cloud. Enhanced by _**_Securonix EON_**_’s AI capabilities, our innovative cloud-native solution delivers a seamless CyberOps experience, empowering organizations to scale their security operations and keep up with evolving threats._
- Recognized as a_**_ five-time leader_**_ in the _**_Gartner Magic Quadrant for SIEM_**_ and highly rated on _**_Gartner Peer Insights_**_, our award-winning Unified Defense SIEM provides organizations with 365 days of ‘hot’ data for rapid search and investigation, threat content-as-a-service, proactive defense through continuous peer and partner collaboration, and a fully integrated _**_Threat Detection, Investigation, and Response (TDIR)_**_ experience—all within a single platform. Built on a cloud-native architecture, the platform leverages the Snowflake Data Cloud for unparalleled scalability and performance._
- Securonix is proud to be a _**_cybersecurity unicorn _**_and featured in CRN's 2024 _**_Security 100 list._**_ Backed by _**_Vista Equity Partners_**_, one of the largest private equity firms with over $100 billion in assets under management, we have a unique advantage in driving innovation and growth. With a global footprint, we serve more than_**_ 1,000 customers_** **_worldwide_**_, including _**_10% of the Fortune 100._**_ Our network of _**_150+ partners_**_ and Managed Security Service Providers (MSSPs) enables us to deliver unmatched security solutions on a global scale._
- At Securonix, we are driven by our core values and place our people at the heart of everything we do:_
- **_ Winning as One Team:_**_ We work together with universal respect to achieve aligned outcomes_
- **_Customer Driven Innovation:_**_ We innovate to stay ahead of the market and create value for our customers_
- **_Agility in Action:_**_ We embrace change and are unified in our purpose and objectives amidst change_
- Join us as we redefine cybersecurity, innovate fearlessly, and grow together as one team._

**Job Summary**:
This position requires a unique blend of technical expertise, research skills, and a deep understanding of large language models (LLMs), machine learning operations (MLOps), and statistical methodologies. As LLMs continue to revolutionize industries, Securonix is at the forefront of leveraging these technologies within the cybersecurity space to develop innovative solutions. Our Threat Science Team is seeking a data scientist to help us build greenfield solutions, implement scalable Generative AI and machine learning systems, and ensure best practices in coding and scripting.

We are seeking a dedicated data scientist with expertise in LLMs, MLOps, and statistical knowledge who can conduct impactful research, develop innovative tools, and collaborate closely both within the team and across product, engineering, and other departments. A background in cybersecurity is preferred but not required. This role is data science-focused, with an emphasis on LLM-based projects, implementing scalable solutions, and new development initiatives.

**Responsibilities**:

- Lead research and implementation of large language models to support security decision-making, greenfield product development, and scalable machine learning solutions.
- Design, deploy, and maintain LLMs for threat detection, automated response, and other security use cases.
- Implement MLOps practices to ensure the reliability, scalability, and efficiency of machine learning workflows.
- Collaborate across teams, including product and engineering, to integrate LLM capabilities into our offerings.
- Support internal and customer-facing initiatives, including proof of concepts (POCs) for new LLM-driven features.
- Establish and enforce coding and scripting best practices to produce robust, maintainable, and production-ready code.
- Conduct statistical and machine learning research to identify potentially malicious activities, leveraging time series analysis, anomaly detection, and unsupervised learning methodologies.

**Qualifications**:

- Master’s degree/PhD (or equivalent) in Statistics, Mathematics, Machine Learning, Computer Science, or other similar quantitative discipline.
- In-depth knowledge of large language models (LLMs), including hands-on experience in implementing, fine-tuning, and optimizing LLMs for specific use cases.
- Proven experience in implementing scalable machine learning systems and integrating them into production environments.
- Proficiency in Python, and familiarity with PySpark, Terraform, Docker, and cloud services such as AWS (EMR, Glue, SageMaker, S3, Bedrock).
- Strong understanding of MLOps principles, including CI/CD pipelines, model monitoring, and a