Data Scientist

Job not on LinkedIn

🔥 9 minutes ago

⚔️ Virginia – Remote

⚔️ Virginia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 12%

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PUNCH Cyber Analytics Group

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🎖️ Defense

🔒 Cybersecurity

Consulting • Defense • Cybersecurity

PUNCH Cyber Analytics Group is a cyber-consulting firm that specializes in advanced analytics and providing strategic support to both government and commercial clients. The company focuses on improving organizational awareness and capability to manage increasing cyber threats. Key services include Security Operations, Threat Intelligence, Incident Response, and Threat Hunting. PUNCH provides custom tool development and supports Security Operations Center analysts from conceptualization to optimization. With a background of monitoring and preventing significant global cyber threats, their services extend to technical analysis and Research & Development in scalable cyber data analysis. They have been awarded a U. S. General Services Administration Schedule 70 contract, facilitating services across federal agencies.

📋 Description

• Develop and evaluate machine-learning analytics for cyber defense use cases using network, sensor, alert, asset, and other operational telemetry • Build unsupervised and statistical models for clustering, anomaly/outlier detection, behavioral baselining, novelty detection, and pattern discovery • Apply graph analytics/embeddings, nearest-neighbor methods, time-series or periodicity analysis, clustering, dimensionality reduction, and anomaly scoring to large cyber datasets • Design models and features accounting for concept drift, noisy data, incomplete ground truth, and high false-positive rates in operational cyber environments • Support asset discovery and entity resolution, including probabilistic asset graphs associating IPs, hostnames, MAC addresses, services, certificates, device attributes, and other observations across data sources • Develop contextual features from security alerts and network telemetry to identify meaningful alert clusters and outliers • Work with cyber analysts and detection engineers to translate operational questions and adversary behaviors into measurable features, experiments, and analytics • Evaluate model effectiveness using quantitative metrics and operational validation; benchmark accuracy, false-positive behavior, computational performance, and usefulness to analysts • Develop production-quality Python code and work with engineers to integrate models into sensor-side CPU environments and GPU-enabled enterprise analytics platforms • Determine when to use LLMs, conventional ML/statistics, or deterministic rules and queries • Build evaluation harnesses with test datasets, expected behaviors, regression tests, failure cases, and quantitative measures

🎯 Requirements

• BS or MS in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Cybersecurity, or a related quantitative discipline • Strong Python skills • Hands-on experience with pandas, NumPy, scikit-learn, SciPy, and related libraries • Strong understanding of unsupervised machine learning, including clustering, anomaly/outlier detection, similarity/distance methods, feature engineering, and statistical baselining • Experience with graph analytics or graph ML, entity resolution/record linkage, probabilistic modeling, time-series analysis, change-point/concept-drift detection, nearest-neighbor methods, or dimensionality reduction • Experience working with large, noisy, heterogeneous datasets where labels or authoritative ground truth are limited • Familiarity with scalable data processing and efficient model implementation • Comfortable thinking about CPU/memory constraints and GPU acceleration for larger workloads • Working knowledge of networking and cybersecurity concepts such as IP addressing, DNS, TLS, network flows, ports/services, routing, network devices, and security alerts • Experience with cyber/network telemetry such as Zeek, PCAP-derived data, SIEM data, IDS/IPS alerts, device configuration data, or vulnerability/asset data is highly desirable • Experience with graph/network-analysis libraries, SQL/data stores, Elasticsearch/Splunk, or similar analytic platforms is a plus • Experience developing analytics for cybersecurity, threat hunting, detection engineering, or defensive cyber operations is strongly preferred

🏖️ Benefits

• Unique benefits and personal touches to provide a positive work-life experience • Inc. Magazine ‘Best Workplaces’ awardee employer