
Data Scientist, Cloudforce One Threat Intelligence
- London
- Permanent
- Full-time
- Collaborate with other Data Scientists and Machine Learning Engineers to design and implement analytical approaches that inform scalable threat detection models.
- Partner with threat intelligence analysts to understand emerging attack techniques and leverage data to develop novel detection strategies and expose findings.
- Perform in-depth data analysis to identify trends, relationships, and anomalies within vast security datasets.
- Develop, validate, and refine statistical and machine learning models for threat detection and intelligence generation.
- Monitor the performance of analytical models and threat intelligence pipelines, continuously identifying opportunities for improvement and refinement.
- Investigate and resolve data-related issues in production environments, ensuring the accuracy and integrity of our threat intelligence.
- Thorough understanding of statistical modeling, hypothesis testing, and various machine learning algorithms, including their strengths and weaknesses across different data types.
- Desire to see a data-driven project through all the way from initial research and experimentation, through model validation, to the delivery of actionable insights and automated processes.
- Demonstrated ability to present complex analytical findings clearly and concisely, and actively solicit and incorporate feedback.
- Proven ability to deliver high-quality analytical work (what) with strong collaborative and problem-solving behaviors (how).
- Experience with large-scale data processing frameworks (e.g., Spark, Flink).
- Experience with time series analysis, anomaly detection, or graph analytics in a security context.
- Proficiency in data visualization tools and techniques to effectively communicate complex findings.
- A basic understanding of the cyber threat landscape and technical Indicators of Compromise (IOCs).
- Experience with Natural Language Processing (NLP) for analyzing unstructured security data.