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# Graduate Data Scientist - Cyber Analytics (Position located in Cheltenham, United Kingdom)

- **Company:** KnowBe4
- **Location:** Cheltenham, UK
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Data Analysis, C Sharp (Programming Language), Data Mining, Python (Programming Language), Logistic Regression, Machine Learning, Tensorflow, Phishing, Standard Sql, Reverse Engineering, Pytorch, Cyber Threat Analysis, Scikit Learn, Information Technology, Vulnerability Analysis
- **Published:** September 26, 2026
- **Apply:** https://www.totaljobs.com/job/data-scientist/knowbe4-job108043565

## About the Role

* Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Physics or a related quantitative field
 * Strong working knowledge of SQL for data extraction and manipulation
 * Demonstrated ability to write clean, efficient code. Proficiency in Python or C#
 * Familiarity with standard ML algorithms (e.g., linear/logistic regression, decision trees, random forests) and libraries like Scikit-Learn or TensorFlow/PyTorch
 * Demonstrable experience in being able to quickly learn and adapt to new areas of technology
 * Ability to think outside the box and/or think maliciously to deliver creative solutions.

## Description

The Cybersecurity Threat Analyst works in the KnowBe4 Threat Research Lab, and is responsible for creating solutions and models to detect threats in KnowBe4's target markets and products.
To learn more about the product this position deals with - click here: https://www.egress.com/products

Responsibilities:

 * Analyzes threat data and implements technical solutions
 * Innovate and create extensions to detection paradigms in end to end fashion
 * Reviewing, understanding and reverse engineering phishing attacks and technologies.
 * Understanding and implementing broader attack vectors.
 * Developing detection algorithms (python, c#) and extracting identifying features of phishing emails.
 * Understanding human behaviour and communications, and how they can be exploited by attackers
 * Using machine learning to identify broader phishing trends and how to protect against them


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