Data Scientist II (Remote)

About the Role:
CrowdStrike’s CTO Labs team is expanding - we are at the exciting intersection of Machine Learning, Big Data, and Security and are looking to add a Data Scientist specializing in machine learning to our growing team.You will have the opportunity to apply your coding, mathematical and scientific research skills to the bleeding edge of security technology. You’ll be able to leverage large-scale rich data to meaningfully improve our supervised learning models and refine our identification of malicious computer software and behavioral threats.  CrowdStrike’s cybersecurity data is one-of-a-kind: we process nearly a trillion behavioural events per day and have over 2000 terabytes of malware samples in our research repository. We are a cross-functional team with deep expertise in Machine Learning, Big Data, and Security.

What You’ll Do:

• Mine large scale and high dimensional data, identify patterns, and visualize trends

• Create predictive models using supervised learning techniques to detect and stop the most sophisticated threats

• Innovate new semi-supervised and online learning techniques to enhance our threat detection capabilities and reduce nuisance false positives for our customers.

• Work closely with domain experts to improve our raw data and to derive more value from data collected

• Hone your ability to balance detail-oriented research with goal-oriented business objectives

• Implement and experiment with new algorithms and methodologies to help improve our machine learning models

• Automate and visualise analyses, results and processes in our machine learning pipeline

What You’ll Need:

• A Master’s degree in Mathematics, Computer Science, Physics, Data Science OR related STEM Field

• Extensive post/undergraduate experience in data science, machine learning, or any field employing computational science or data driven analyses

• Programming experience in Python

• 2+ year’s experience working on real world machine learning models and pipelines

Bonus Points:

• Passionate about cybersecurity, with a firm understanding of the problem space or passionate about applying your machine learning skillset to new domain areas such as cybersecurity

• Versed in utilising Machine Learning techniques and familiar with the standard algorithms, their trade-offs, their usage, and how to tune them

• Have experience working on very large data sets of sparse high dimensional data and experience in pre-processing and analysing such data to gain actionable insights

• An independent self-starter who likes to take ownership and independently seeks out new challenges

• Thirsty for knowledge and do not hesitate to step outside of your comfort zone to learn new technologies, algorithms and concepts

• Comfortable to dive into a Python codebase, including experience with unit testing and the python packaging ecosystem

• Comfortable and experienced working in a Linux environment in the AWS cloud

• Analytically minded: never afraid to drill down into a data-set, or debug-deeper into an unfamiliar codebase