Security Data Scientist--Duo Security

Key Skills

Data science techniques, Machine learning techniques, Python Programming, R Programming

Job Description

As a Lead Security Data Scientist on the Duo AI and Security Research team, you will build systems to detect, mitigate, and prevent identity cyber threats affecting our customers. You will collaborate with teams in the Data Science & Engineering organization to improve our existing Trust Monitor and Risk-based Authentication systems, while working to develop the next generation of machine learning and data driven enhancements for Duo’s product. You will combine knowledge of Data Science with curiosity about adversarial techniques to help deliver best-in-class security outcomes.

Responsibilities include:

• Develop, evaluate, and refine algorithms for detecting cyber threats in large scale customer telemetry
• Collaborate with Product, Engineering, and Design teams to implement systems for real-time mitigation of detected threats
• Investigate the latest tactics, techniques, and procedures in identity security in conjunction with threat intelligence teams in Cisco Talos
• Lead the construction of labeled threat datasets and guide their use in machine learning applications
• Understand the link between access and authentication policies and security outcomes and design algorithms to guide customers to improve their security posture
• Represent a Data Science perspective during product development, helping teams appropriately prioritize data collection, feedback loops, and other prerequisites for future data work

Minimum Experience Required for this Role:

• 6+ years professional experience in data science, analytics, or quantitative intelligence analysis
• 4+ years experience in at least one data analysis and modeling language (like Python or R), including 2+ years experience with Python
• Development experience of machine learning models in a business setting
• Experience with cybersecurity or an adjacent domain such as fraud protection.
• Leading applied research within a team and/or experience mentoring junior data scientists

Preferred Experience:

• Application of data science tools to tackle problems in the security domain
• Graduate level education in statistics, data science, machine learning, computational sciences or similar
• Software Engineering training or experience, and comfort working with the AWS ecosystem
• Experience with large-scale data processing frameworks such as Spark
• Experience working on a customer-facing SaaS product
• Prioritizing and planning research work with collaborators such as engineering, product, and design teams

Why Cisco Secure:

We're global, we're adaptable, we're diverse, and our security portfolio is as extensive as it is groundbreaking. Have you heard of Threat, Detection & Response, Zero Trust by Duo, Common Services Engineering, or Cloud & Network Security? Those are only a few of our product teams! The only thing we're missing is YOU.

Join an enterprise security leader with a start-up culture, committed to driving innovation and giving you the opportunity to make an impact. We #InnovateToWin and we know we're better together, that's why we're dedicated to inclusivity, collaboration, and diversity in everything we do.

We're proud to be the Best Small and Mid-Size Enterprises Security Solution Cisco Secure continues to grow and evolve year after year with 100% of Fortune 100 Companies using our products, and we're excited to see the new heights we'll reach with your passion for security, your customer focus, and your desire to change things up!

There are so many amazing reasons to join Cisco. Learn more

here!

Message to applicants applying to work in the U.S. and/or Canada:

When available, the salary range posted for this position reflects the projected hiring range for new hire, full-time salaries in U.S. and/or Canada locations, not including equity or benefits. For non-sales roles the hiring ranges reflect base salary only; employees are also eligible to receive annual bonuses. Hiring ranges for sales positions include base and incentive compensation target. Individual pay is determined by the candidate's hiring location and additional factors, including but not limited to skillset, experience, and relevant education, certifications, or training. Applicants may not be eligible for the full salary range based on their U.S. or Canada hiring location. The recruiter can share more details about compensation for the role in your location during the hiring process.