Senior Data Scientist – Payload & SAT-RAN
מעבר למשרות נוספות גוב פלייס
פורסם לפני 1 ימים
- פתח תקווה
- משרה מלאה
- לא צוין שכר
תיאור המשרה:
Own Payload / GW / SAT-RAN data strategy: define key subsystem metrics, data sources, and collection requirements spanning payload, gateway, transport, and RAN/service layers
Design and maintain SAT-RAN subsystem data models (entities, relationships, identifiers etc) to unify telemetry across domains and support scalable analytics
Lead data model definition and deployment into production systems: instrumentation requirements, pipeline design, validation, versioning, and data quality monitoring
Develop performance analytics for overall end-to-end Satellite–RAN performance projected over multiple subsystems, including attribution of impact across payload, GW, transport, core, and RAN layers
Build failure/anomaly detection and prevention systems using multivariate time-series, correlation/causality-informed approaches, topology/context-aware features, and alert deduplication/triage scoring
Create qualitative quality scoring models that combine predictive signals with measured KPIs/KQIs, including confidence/uncertainty measures
Develop fleet service scheduling models, linking orbital state/visibility, predicted SAT-RAN capacity and quality, interference, and spacecraft power/thermal constraints to achievable service performance and demand fulfillment.
Build decision-support data products: dashboards, health scores, early-warning indicators, incident enrichment, and executive-ready reporting for SAT-RAN performance
Partner with engineering teams to define success metrics, run backtesting/regression evaluation, and operationalize models into workflows (assurance, release validation, optimization loops)
Establish best practices for reproducibility and MLOps: model monitoring, drift detection, dataset/version governance, and documentation
Design and maintain SAT-RAN subsystem data models (entities, relationships, identifiers etc) to unify telemetry across domains and support scalable analytics
Lead data model definition and deployment into production systems: instrumentation requirements, pipeline design, validation, versioning, and data quality monitoring
Develop performance analytics for overall end-to-end Satellite–RAN performance projected over multiple subsystems, including attribution of impact across payload, GW, transport, core, and RAN layers
Build failure/anomaly detection and prevention systems using multivariate time-series, correlation/causality-informed approaches, topology/context-aware features, and alert deduplication/triage scoring
Create qualitative quality scoring models that combine predictive signals with measured KPIs/KQIs, including confidence/uncertainty measures
Develop fleet service scheduling models, linking orbital state/visibility, predicted SAT-RAN capacity and quality, interference, and spacecraft power/thermal constraints to achievable service performance and demand fulfillment.
Build decision-support data products: dashboards, health scores, early-warning indicators, incident enrichment, and executive-ready reporting for SAT-RAN performance
Partner with engineering teams to define success metrics, run backtesting/regression evaluation, and operationalize models into workflows (assurance, release validation, optimization loops)
Establish best practices for reproducibility and MLOps: model monitoring, drift detection, dataset/version governance, and documentation
דרישות המשרה:
Minimum Qualifications
5+ years of experience delivering data science / ML solutions in production (monitoring, anomaly detection, forecasting, quality scoring, optimization support)
Strong proficiency in Python (pandas/NumPy/scikit-learn and time-series tooling) and strong SQL skills
Demonstrated experience defining and operating data models and analytics pipelines (schemas, identifiers, aggregation logic, data validation, lineage)
Strong statistical foundations (model evaluation, uncertainty, time-series behavior, bias/variance, backtesting)
Ability to translate cross-domain system problems into measurable metrics and deployable analytics
Bachelor’s or Master’s degree in CS/EE/Statistics/Math/Physics or related technical field (or equivalent experience)
Preferred Qualifications
Multivariate anomaly detection at scale (change-point detection, sequence models where justified, graph/topology-aware features)
Telecom/systems experience: LTE/5G KPIs/KQIs, OSS counters/alarms, QoE/QoS metrics, RAN performance indicators
Familiarity with scheduling/capacity modeling concepts (resource allocation, interference-aware capacity, constraint modeling, power/thermal-limited regimes)
MLOps experience (deployment, monitoring, drift, CI/CD for data + models) and
5+ years of experience delivering data science / ML solutions in production (monitoring, anomaly detection, forecasting, quality scoring, optimization support)
Strong proficiency in Python (pandas/NumPy/scikit-learn and time-series tooling) and strong SQL skills
Demonstrated experience defining and operating data models and analytics pipelines (schemas, identifiers, aggregation logic, data validation, lineage)
Strong statistical foundations (model evaluation, uncertainty, time-series behavior, bias/variance, backtesting)
Ability to translate cross-domain system problems into measurable metrics and deployable analytics
Bachelor’s or Master’s degree in CS/EE/Statistics/Math/Physics or related technical field (or equivalent experience)
Preferred Qualifications
Multivariate anomaly detection at scale (change-point detection, sequence models where justified, graph/topology-aware features)
Telecom/systems experience: LTE/5G KPIs/KQIs, OSS counters/alarms, QoE/QoS metrics, RAN performance indicators
Familiarity with scheduling/capacity modeling concepts (resource allocation, interference-aware capacity, constraint modeling, power/thermal-limited regimes)
MLOps experience (deployment, monitoring, drift, CI/CD for data + models) and
מעבר למשרות דומות בתחומים:
משרה מספר 9914677
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