Senior Data Scientist

extrahopnetworks; United States; Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Flexible PTO

Annual discretionary bonus

FSA and dependent care accounts

Educational reimbursement

401(k) with employer match

Pet insurance

Parental leave

Hybrid and remote work model

Job summary

extrahopnetworks is seeking a Senior Data Scientist to join a cybersecurity team building Network Detection and Response capabilities across hybrid infrastructure. You will apply statistics, experimentation, and machine learning to large-scale network telemetry.

You will collaborate with data scientists, threat researchers, and engineers to turn research into reliable product features, write production-grade code, and communicate results to stakeholders.

Qualifications

• Bachelor's degree in Data Science, Computer Science, Mathematics, or another quantitative discipline, or equivalent practical experience.
• 7+ years of professional data science experience building and evaluating ML models for real-world use cases.
• Strong foundation in statistics, experimental design, machine learning, and model evaluation.
• Experience working with incomplete, noisy, or highly imbalanced data and performing detailed error analysis.
• Strong proficiency in Python and SQL, plus common data science and ML libraries.
• Experience partnering with software engineers to ship data science work into production systems.
• Strong problem-solving skills, intellectual curiosity, and a track record of independently owning complex technical work.
• Excellent written and verbal communication skills, including explaining technical findings and uncertainty to varied audiences.

Responsibilities

• Analyze large-scale network telemetry to surface behavioral patterns, anomalies, and signals tied to malicious activity.
• Design, develop, and refine machine learning and AI methods that detect threats in real time.
• Build evaluation approaches suited to cybersecurity data, including imbalanced datasets, incomplete labels, rare events, and shifting attacker behavior.
• Perform exploratory analysis, feature engineering, model development, and error analysis on complex, high-volume datasets.
• Research emerging ML and AI techniques and assess applicability to existing detection products.
• Define metrics and monitoring strategies that track model and detector performance over time.
• Communicate findings, limitations, and tradeoffs to technical stakeholders and product leaders.
• Mentor other data scientists through code reviews, design discussions, and contributions to team standards.
• Document methodologies, experiments, and evaluation results.
• Write clean, maintainable, well-tested production code.

Skills

Statistics

Experimental design

Machine learning

Model evaluation

Python

SQL

ML libraries

Error analysis

Communication

Education

Bachelor's degree in Data Science, Computer Science, Mathematics, or related field

Master's degree in Data Science, CS, Mathematics, or related field

PhD in Data Science, CS, Mathematics, or related field

Tools

scikit-learn

TensorFlow

PyTorch

Jupyter

Job description

Role overview

Join a cybersecurity team building Network Detection and Response capabilities that help organizations investigate and stop threats across hybrid infrastructure. As a Senior Data Scientist, you will work on ambiguous, high-impact problems by applying statistical analysis, experimentation, and machine learning to large-scale network telemetry. This is an applied role partnering closely with other data scientists, threat researchers, and engineers to turn research into reliable product features.

Responsibilities

• Analyze large-scale network telemetry to surface behavioral patterns, anomalies, and signals tied to malicious activity.
• Design, develop, and refine machine learning and AI methods that detect threats in real time.
• Build evaluation approaches suited to cybersecurity data, including imbalanced datasets, incomplete labels, rare events, and shifting attacker behavior.
• Perform exploratory analysis, feature engineering, model development, and error analysis on complex, high-volume datasets.
• Research emerging ML and AI techniques and assess applicability to existing detection products.
• Define metrics and monitoring strategies that track model and detector performance over time.
• Communicate findings, limitations, and tradeoffs to technical stakeholders and product leaders.
• Mentor other data scientists through code reviews, design discussions, and contributions to team standards.
• Document methodologies, experiments, and evaluation results.
• Write clean, maintainable, well-tested production code.

Requirements

• Bachelor's degree in Data Science, Computer Science, Mathematics, or another quantitative discipline, or equivalent practical experience.
• 7+ years of professional data science experience building and evaluating ML models for real-world use cases.
• Strong foundation in statistics, experimental design, machine learning, and model evaluation.
• Experience working with incomplete, noisy, or highly imbalanced data and performing detailed error analysis.
• Strong proficiency in Python and SQL, plus common data science and ML libraries.
• Experience partnering with software engineers to ship data science work into production systems.
• Strong problem-solving skills, intellectual curiosity, and a track record of independently owning complex technical work.
• Excellent written and verbal communication skills, including explaining technical findings and uncertainty to varied audiences.

Nice to have

• Master's degree or Ph.D. in Data Science, Computer Science, Mathematics, or a related quantitative field.
• Experience applying data science to security, networking, or related domains.

Benefits and work setup

• Health, dental, and vision coverage for employees and families.
• Flexible PTO, prorated sick time, federal holidays, and paid volunteer days.
• Eligibility for an annual discretionary bonus plan for non-commissioned roles.
• FSA and dependent care accounts, plus an employee assistance program where applicable.
• Educational reimbursement and a 401(k) with employer match or pension where applicable.
• Pet insurance and parental leave.
• Hybrid and remote work model.