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Job details
As a Staff Data Scientist at Calix, you will apply advanced analytics and machine learning to broadband access network, service, and subscriber telemetry data.
You will work closely with senior data scientists, engineers, and product teams to build models and insights that power network intelligence, service assurance, and subscriber experience analytics within Calix’s cloud platforms.
Requirements
Analyze and model large-scale broadband telemetry and time-series data used by Calix cloud, including throughput, latency, packet loss, utilization, and device-level metrics, and many more. Develop and validate ML models for Upsell, cross-sell, churn prevention, customer acquisition, anomaly detection, performance forecasting, fault classification, and capacity prediction that drive proactive network insightsBuild features and models supporting network health scoring, service quality monitoring, and subscriber Quality of Experience (QoE) analyticsCollaborate with data engineering and platform teams to develop and integrate models into Calix Cloud’s cloud-native analytics pipelinesPerform EDA, feature engineering, and data preprocessing for scalable, production pipelinesHelp scale analytics and ML solutions across millions of access devices, subscriber endpoints, and Wi-Fi environmentsDesign experiments and evaluate the business and operational impact of analytics on network performance and subscriber experienceBuild scalable ML pipelines and deploy models into production environments. Communicate insights clearly to product, engineering, and customer-facing teams via dashboards, reports, and presentationsTranslate ambiguous product and operational problems into well-defined data science and ML solutionsFollow best practices in model lifecycle management, including versioning, validation, and deployment monitoring
Benefits
BonusTotal compensation package.
You will work closely with senior data scientists, engineers, and product teams to build models and insights that power network intelligence, service assurance, and subscriber experience analytics within Calix’s cloud platforms.
Requirements
Analyze and model large-scale broadband telemetry and time-series data used by Calix cloud, including throughput, latency, packet loss, utilization, and device-level metrics, and many more. Develop and validate ML models for Upsell, cross-sell, churn prevention, customer acquisition, anomaly detection, performance forecasting, fault classification, and capacity prediction that drive proactive network insightsBuild features and models supporting network health scoring, service quality monitoring, and subscriber Quality of Experience (QoE) analyticsCollaborate with data engineering and platform teams to develop and integrate models into Calix Cloud’s cloud-native analytics pipelinesPerform EDA, feature engineering, and data preprocessing for scalable, production pipelinesHelp scale analytics and ML solutions across millions of access devices, subscriber endpoints, and Wi-Fi environmentsDesign experiments and evaluate the business and operational impact of analytics on network performance and subscriber experienceBuild scalable ML pipelines and deploy models into production environments. Communicate insights clearly to product, engineering, and customer-facing teams via dashboards, reports, and presentationsTranslate ambiguous product and operational problems into well-defined data science and ML solutionsFollow best practices in model lifecycle management, including versioning, validation, and deployment monitoring
Benefits
BonusTotal compensation package.
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The company
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Calix Canada, United States
