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 insights.
Build features and models supporting network health scoring, service quality monitoring, and subscriber Quality of Experience (QoE) analytics.
Apply advanced techniques such as time-series modeling, change-point detection, and probabilistic modeling to real-world broadband data.
Collaborate with data engineering and platform teams to develop and integrate models into Calix Cloud’s cloud-native analytics pipelines.
Perform EDA, feature engineering, and data preprocessing for scalable, production pipelines.
Help scale analytics and ML solutions across millions of access devices, subscriber endpoints, and Wi-Fi environments.
Design experiments and evaluate the business and operational impact of analytics on network performance and subscriber experience.
Build scalable ML pipelines and deploy models into production environments.
Communicate insights clearly to product, engineering, and customer-facing teams via dashboards, reports, and presentations.
Translate ambiguous product and operational problems into well-defined data science and ML solutions.
Follow best practices in model lifecycle management, including versioning, validation, and deployment monitoring.

Requirements

PhD (completed or near completion) in Data Science, Computer Science, or related degree.
Strong foundation in statistics, probability, and linear algebra.
Experience working with large-scale time-series and telemetry datasets typical of broadband analytics.
Hands-on experience with ML techniques, including: Regression and classification, Clustering and dimensionality reduction, Time-series analysis and forecasting, Anomaly detection and change-point detection.
Experience with model evaluation, validation methods, and performance metrics.
Strong programming skills in Python and familiarity with ML libraries: NumPy, pandas, SciPy, scikit-learn.
Strong SQL skills for large-scale data analysis.
Ability to write clean, maintainable, and testable code.
Experience with data preprocessing, feature engineering, and exploratory data analysis (EDA).
Experience in analyzing broadband network and service telemetry.
Ability to work with metrics such as latency, throughput, packet loss, utilization, and device-level signals.
Understanding of noisy, incomplete, and delayed data common in broadband environments.
Ability to reason about data across devices, subscribers, locations, and time windows.
Strong problem-solving skills and ability to translate ambiguous product or network problems into analytical solutions.
Clear written and verbal communication skills.
Experience presenting insights through charts, dashboards, and reports.

Benefits

As a part of the total compensation package, this role may be eligible for a bonus.
For information on our benefits click here.

Applicant Tracking System Keywords

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

Hard Skills & Tools

machine learningtime-series analysisanomaly detectionchange-point detectionfeature engineeringexploratory data analysisPythonSQLNumPyscikit-learn

Soft Skills

problem-solvingcommunicationcollaborationdata reasoninganalytical thinkingpresentation skillsclean code writingmodel lifecycle managementvalidationdeployment monitoring

Certifications

PhD in Data SciencePhD in Computer Science