Data Scientist Team Lead
New
J
JobgetherCybersecurity Analytics
Based in the United StatesFull-TimeLead
SalaryCompetitive salary paid twice per month.
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonCybersecurityKubernetesMachine LearningData engineeringData scienceData visualization
Requirements
- Master’s or PhD in a quantitative discipline such as Statistics, Engineering, Computer Science, Economics, or a related field; additional relevant experience may be considered in lieu of the education requirement on a year-for-year basis.
- 5+ years of experience in machine learning engineering, data science, data engineering, software development for data solutions, or a related discipline.
- Demonstrated experience designing technical solutions and leading teams through implementation of those solutions.
- Strong programming experience with object-oriented languages such as Python, JSON, C++, Java, R, or Scala.
- Experience with containerization technologies including Docker and Kubernetes.
- Proven ability to architect and develop novel analytical methods using machine learning techniques.
- Experience developing data-driven cybersecurity solutions, including machine learning algorithms, data models, and architecture strategies for cyber defense.
- Experience engineering data workflows that combine disparate sources and generate actionable, data-driven insights.
- Experience designing automation for security tool management, customized searches, and cybersecurity applications.
- Strong understanding of cybersecurity data, threat detection, security analytics, and enterprise-scale data environments.
- Certified Analytics Professional (CAP) certification is required.
Responsibilities
- Lead the design and implementation of technical data science solutions supporting enterprise cybersecurity operations.
- Guide teams in developing data models, machine learning capabilities, analytical workflows, and automation for security monitoring, threat detection, threat hunting, UEBA, and cyber intelligence.
- Design custom algorithms, analytical processes, and data architectures for large-scale datasets used in modeling, data mining, research, and cyber defense.
- Develop machine learning models to identify anomalous behavior, emerging threats, attack patterns, and other indicators of malicious activity.
- Create metrics, trend analyses, dashboards, and visualizations that communicate cybersecurity risks, anomalies, threat activity, and analytical findings to technical and leadership audiences.
- Design automation for security tool administration, cybersecurity analytics, customized searches, and security applications.
- Collaborate with cybersecurity specialists across security operations, threat intelligence, threat hunting, penetration testing, digital forensics, and engineering.
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