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Threat Analyst, Machine Learning; Remote, East

Remote / Online - Candidates ideally in
Coos Bay, Coos County, Oregon, 97458, USA
Listing for: CrowdStrike
Remote/Work from Home position
Listed on 2026-01-19
Job specializations:
  • IT/Tech
    Cybersecurity
Salary/Wage Range or Industry Benchmark: 125000 USD Yearly USD 125000.00 YEAR
Job Description & How to Apply Below
Position: Threat Analyst, Machine Learning (Remote, East/Central)

Employer Industry: Cybersecurity

Why consider this job opportunity:
  • Salary up to $125,000 per year
  • Eligibility for bonuses and equity grants
  • Comprehensive physical and mental wellness programs
  • Competitive vacation and holidays for recharge
  • Professional development opportunities for all employees
  • Remote work flexibility
What to Expect (Job Responsibilities):
  • Review current product detections to ensure they are performing to company standards
  • Perform tasks to enable better management of false positive detections
  • Analyze binary files to determine their legitimacy
  • Address internal questions and concerns regarding customer threat detections
  • Collaborate with internal teams such as Technical Account Managers and Data Scientists
What is Required (Qualifications):
  • Exposure and understanding of different types and functionality of malware
  • Experience with reverse engineering malware or malware operations
  • Knowledge of programming and scripting languages, particularly Python
  • Fundamental understanding of attributes of binary files such as imports/exports and packers
  • General understanding of threat/risk management and threat/risk assessment
How to Stand Out (Preferred Qualifications):
  • Experience in a security operations center or similar environment responding to incidents
  • A thorough understanding of Windows OS internals and the Windows API
  • Familiarity with tools used in targeted and criminal cyber-intrusions
  • Knowledge of a variety of programming languages including C, C++, Java, and assembly
  • Experience with threat detections by machine learning
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