Data Scientist

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 ation