Build and operationalize models for anomaly detection, forecasting, early incident warning, performance regression detection, saturation/capacity risk, and service health scoring.
Correlate logs/metrics/traces/events with topology, deployment, change, and business signals to identify drivers of degradation and reduce time-to-diagnosis.
Prototype and advance agentic workflows that assist with triage, signal enrichment, event clustering, summarization, and guided next-best-action recommendations.
Use and extend enterprise observability platforms (Splunk, Datadog, Cribl, SolarWinds, Langfuse) to extract signals, engineer features, validate hypotheses, and operationalize outcomes.
Define data quality checks, feature pipelines, and scalable methods for working with high-volume telemetry (batch and/or streaming), partnering with platform teams as needed.
Establish model performance measures aligned to operational goals (noise reduction, precision/recall of detections, lead time to failure, MTTR improvements); monitor drift and iterate.
Communicate findings to technical and non-technical stakeholders with clear recommendations, tradeoffs, and measurable results.
Ensure solutions align with Leidos standards for security, privacy, governance, and responsible AI practices.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or related field with 12+ years relevant experience (additional experience may be considered in lieu of degree).
Demonstrated large-scale observability analytics/AIOps experience working with high-volume telemetry (logs, metrics, traces, events) in complex enterprise environments.
Strong programming skills in Python and experience with ML/data science libraries (e.g., pandas, NumPy, scikit-learn; deep learning frameworks a plus).
Proven delivery of predictive analytics solutions such as time-series forecasting, anomaly detection, clustering, classification, and statistical modeling.
Ability to move from ambiguous problem statements to working analytics in production-like environments.
Excellent written and verbal communication skills; ability to translate analytical output into operational and business impact.

Benefits

competitive compensation
Health and Wellness programs
Income Protection
Paid Leave
Retirement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

anomaly detectionforecastingperformance regression detectiondata quality checksfeature pipelinespredictive analyticstime-series forecastingclusteringclassificationstatistical modeling

Soft skills

communication skillsproblem-solvingstakeholder engagementanalytical thinkingcollaboration