Data Scientist Team Lead
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist Team Lead based in the United States.
This role offers an opportunity to lead advanced data science initiatives at the intersection of machine learning, cybersecurity, and enterprise analytics.
You will design technical solutions that transform large, complex security datasets into actionable intelligence and defensive capabilities.
Working closely with security operations, threat hunting, intelligence, forensics, penetration testing, and engineering teams, you will help strengthen enterprise cyber defense.
The position combines hands-on technical work with team leadership, architectural design, automation, and analytical innovation.
You will develop machine learning models, data pipelines, predictive analytics, and visualization capabilities that identify threats and uncover anomalous behavior.
Your work will contribute to improving detection, investigation, response, risk analysis, and proactive security operations at enterprise scale.
This is an impactful opportunity for a technically strong data science leader who wants to apply advanced analytics to complex cybersecurity challenges.
Accountabilities
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 advanced analytics for predictive risk analysis, risk identification and mapping, cyber risk cost analysis, supply chain threat identification, and User and Entity Behavior Analytics.
Design and implement data pipelines capable of ingesting, normalizing, correlating, and analyzing information from diverse security and enterprise data sources.
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.
Apply data science and automation to threat hunting activities to improve analytical maturity and reduce manual investigation.
Incorporate predictive modeling into operational threat hunting and threat simulations to estimate attack probability, potential impact, and associated costs.
Correlate cyber threat intelligence with assets, users, and security events to assess the financial and operational implications of potential incidents.
Develop custom Indicators of Compromise and Indicators of Attack detection and alerting capabilities.
Design automation for security tool administration, cybersecurity analytics, customized searches, and security applications.
Support integration of analytical capabilities with Security Information and Event Management and Security Orchestration, Automation, and Response platforms.
Support the development, integration, optimization, and maintenance of User and Entity Behavior Analytics capabilities.
Identify and resolve data quality, integrity, architecture, and analytical issues affecting cybersecurity solutions.
Establish repeatable and scalable analytical processes that improve detection, investigation, response, and proactive defense operations.
Collaborate with cybersecurity specialists across security operations, threat intelligence, threat hunting, penetration testing, digital forensics, and engineering.
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.
Ability to develop high-visibility cybersecurity reporting through data visualization, dashboards, and analytical reporting.
Strong understanding of cybersecurity data, threat detection, security analytics, and enterprise-scale data environments.
Strong analytical, problem-solving, communication, and technical leadership skills.
Ability to collaborate effectively with multidisciplinary cybersecurity and technical teams.
Certified Analytics Professional (CAP) certification is required.
Must be eligible to obtain or maintain a Secret security clearance.
Competitive salary paid twice per month.
Comprehensive medical coverage.
100% of medical premiums covered by the employer.
Company-wide new business incentive programs.
Additional contribution incentives for activities such as white papers, blog posts, and internal webinars.
3 weeks of PTO starting annually.
11 paid holidays per year.
401(k) program with a 100% employer match on the first 4%.
Monthly reimbursement for cell phone and home internet expenses.
Paid maternity and paternity leave.
Investment in professional training and industry certifications.
Opportunities to deepen and broaden technical expertise in data science, machine learning, and cybersecurity.
Opportunity to lead high-impact cybersecurity analytics initiatives in a technically sophisticated environment.