Manager, Data Science; Remote

#We Are Crowd Strike  and our mission is to stop breaches. As a global leader in cybersecurity, our team changed the game. Since our inception, our market leading cloud-native platform has offered unparalleled protection against the most sophisticated cyberattacks. We’re looking for people with limitless passion, a relentless focus on innovation and a fanatical commitment to the customer to join us in shaping the future of cybersecurity.

Consistently recognized as a top workplace, Crowd Strike is committed to cultivating an inclusive, remote-first culture that offers people the autonomy and flexibility to balance the needs of work and life while taking their career to the next level. Interested in working for a company that sets the standard and leads with integrity? Join us on a mission that matters - one team, one fight.

Crowd Strike’s Data Science team is expanding -- we are at the exciting intersection of Machine Learning, Artificial Intelligence, and Security and are looking to add a Data Science Manager 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.

Crowd Strike’s cybersecurity data is one-of-a-kind: we process over 1 trillion behavioral events per day and have petabytes of malware samples in our research repository. We are a diverse and multidisciplinary team, and you’ll have the chance to broaden your horizons by working jointly with a team of Big Data, Machine Learning, and Security domain experts on hard and impactful problems.

Crowd Strike has always been industry pioneer in its use of Machine Learning and Artificial Intelligence: from our first to market use of ML for malware classification, to our cutting-edge Generative AI powered natural-language interface, Charlotte.

• Build a team of machine learning practitioners that can balance detail-oriented research with goal-oriented business objectives
• 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
• Implement and experiment with new algorithms and methodologies to help improve our machine learning models
• Automate and visualize analyses, results and processes in our machine learning pipeline

• Undergraduate or post-graduate degree in a STEM field
• 8+ Years of post-undergraduate experience in data science, machine learning, or any field employing computational science or data driven analyses
• 2+ Years of direct management experience, or several years of ‘dotted-line’ leadership experience
• Programming experience in Python, Rust, R, or Mat Lab to match (preference in that order); must be comfortable and experienced working in a Linux environment in the AWS cloud and have an appreciation for the software development lifecycle and best practices
• An independent self-starter who likes to take ownership and independently seeks out new challenges; someone who is thirsty for knowledge and do not hesitate to step outside of your comfort zone to learn new technologies, algorithms and concepts
• Experience working on very large data sets of sparse high dimensional data and experience in pre-processing and analyzing such data to gain actionable insights
• 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 utilizing Machine Learning techniques for consumer software products, including the development of KPIs for managing product success.
• A security industry veteran, with experience building classifiers to identify malware…