Cybersecurity Data Scientist

Impact Advisors

1d • $95,000 - $180,000

About The Position

Impact Advisors is building a security product for health systems, and this is a founding role on the product. The Cybersecurity Data Scientist will own the analytical layer end to end, from profiling varied and often unstructured source data through feature development, modeling, evaluation, deployment, and ongoing operation. The role focuses on behavioral modeling at scale: establishing baselines across large populations, detecting deviations, and delivering models that perform reliably in production within customer environments. Candidates should have experience in cybersecurity or an adjacent domain with similar problems, such as fraud, abuse, payments risk, or insider risk. The position includes 25% travel to clients.

Requirements

• Bachelor's degree or higher in engineering, mathematics, statistics, or computer science.
• At least 5 years applying data science to a security, fraud, abuse, or risk domain, including models deployed to production.
• Advanced proficiency in Python and SQL, with experience at data volumes where tooling selection affects outcomes.
• Demonstrated anomaly detection experience, including population baselining, peer-group comparison, and data-derived thresholds.
• Ability to reason about base rates and alert volume, including deriving required precision from population size and alert capacity.
• Experience building data pipelines.
• Experience deploying and maintaining production models, including versioning, monitoring, and retraining.
• Hands-on experience applying language models in production.
• Clear written and verbal communication of technical findings to non-technical audiences.

Responsibilities

• Profile unfamiliar data, assess what it supports, and establish baselines for users, roles, devices, and systems.
• Develop detection and scoring approaches using suitable methods, including peer-group comparison, clustering, classification, outlier detection, and time series.
• Tune models against production data, reduce false positives without losing coverage, and maintain performance as underlying systems change.
• Define evaluation criteria, measurement methods, and drift detection.
• Build the data path supporting models, from ingestion and normalization through reliably computed features.
• Own deployment and ongoing operation of models in production.
• Develop visualizations that help customer security leads interpret and challenge model output.
• Select and justify appropriate approaches for each task across statistical methods, classical machine learning, and language models.
• Apply small and local models when deployment constraints require them.
• Use AI coding tools as part of standard development practice.
• Travel to clients 25% of the time.

Benefits

• May be eligible for an annual performance bonus; eligibility depends on position and employment terms.
• Additional benefits and perks may be available depending on the position and employment terms.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior