Senior Data Scientist

Job not on LinkedIn

🕒 August 21

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 18%

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Logo of CISPA Helmholtz Center for Information Security

CISPA Helmholtz Center for Information Security

501 - 1000 employees

Founded 2011

💼 Consulting

🎖️ Defense

🏥 Healthcare

Consulting • Defense • Healthcare

CISPA Helmholtz Center for Information Security is a national Big Science institution within the Helmholtz Association of German Research Centers. It explores information security in all its facets to address major challenges in cybersecurity and trustworthy artificial intelligence. Renowned for its cutting-edge foundational and applied research, CISPA aims to cover the full spectrum from theoretical insights to empirical studies, positioning itself as a global leader in the cybersecurity field and a training ground for the next generation of experts and leaders in the domain.

📋 Description

• Own models and data end to end, including problem framing, feature engineering, training, evaluation, deployment, and explaining model results to customers • Design, train, and ship exploit prediction models using ground-truth exploitation telemetry across cloud, appsec, and traditional infrastructure • Build evaluation using precision, recall, coverage, efficiency, and calibration, including how these metrics decay over time • Address extreme class imbalance in vulnerability exploitation prediction • Develop the dual-model architecture using partial pooling, hierarchical priors, and cold-start behavior for customers with limited local telemetry • Engineer features across scanner output, EDR, asset inventory, identity, cloud posture, and exploitation telemetry, while identifying data leakage • Own monitoring and drift detection • Publish papers, methodology write-ups, open benchmarks, and conference talks • Partner with engineering and the forward deployed team to move models from notebooks into production systems used by customers • Explain vulnerability model rankings and uncertainty to security executives and customers

🎯 Requirements

• Several years of applied machine learning or statistics with models that ran in production and had consequences when they were wrong • Fluency in Python and SQL • Version control and reproducible pipelines • Secure handling of customer data • Real depth in classification under heavy imbalance • At least one of: survival and time-to-event analysis, Bayesian hierarchical modeling, or causal inference • Ability to explain a model to a security executive • Ability to quantify uncertainty • Curiosity about attacker behavior • Marginalized communities, including women, LGBTQ+ people, and people of color, are encouraged to apply even if they do not meet every qualification

🏖️ Benefits

• Inclusive, diverse, equitable, and accessible workplace • Workplace that fosters a sense of belonging

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