Staff Data Scientist
The Calix platform enables Communication Service Providers (CSPs) of all sizes to transform and future-proof their businesses. Through real-time data, automation, and actionable insights delivered via Calix One — our cloud-first, AI-powered platform — CSPs can simplify operations, collapse cost, and accelerate innovation. Calix One brings together the automation of everything and the experience of one, empowering customers to deliver differentiated subscriber experiences while driving acquisition, loyalty, and revenue growth. This is the Calix mission: to enable CSPs of all sizes to simplify, innovate, and grow, strengthening both their businesses and the communities they serve.
We’re at the forefront of a once in a generational change in the broadband industry. Join us as we innovate, help our customers reach their potential, and connect underserved communities with unrivaled digital experiences. Role Overview
As a Staff Data Scientist focused on Calix Cloud and Intelligence, 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.
Key Responsibilities
Calix Cloud - Analytics & AI
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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.
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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
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Build features and models supporting network health scoring, service quality monitoring, and subscriber Quality of Experience (QoE) analytics
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Apply advanced techniques such as time-series modeling, change-point detection, and probabilistic modeling to real-world broadband data
Calix Cloud - Platform & Scale
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Collaborate with data engineering and platform teams to develop and integrate models into Calix Cloud’s cloud-native analytics pipelines
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Perform EDA, feature engineering, and data preprocessing for scalable, production pipelines
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Help scale analytics and ML solutions across millions of access devices, subscriber endpoints, and Wi-Fi environments
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Design experiments and evaluate the business and operational impact of analytics on network performance and subscriber experience
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Build scalable ML pipelines and deploy models into production environments.
Communication & Product Collaboration
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Communicate insights clearly to product, engineering, and customer-facing teams via dashboards, reports, and presentations
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Translate ambiguous product and operational problems into well-defined data science and ML solutions
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Follow best practices in model lifecycle management, including versioning, validation, and deployment monitoring
Required Qualifications & Technical Skills
Education
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PhD in Data Science or Computer Science is preferred
Data Science & Machine Learning
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Strong foundation in statistics, probability, and linear algebra
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Experience working with large-scale time-series and telemetry datasets typical of broadband analytics
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Hands-on experience with ML techniques, including:
- Regression and classification
- Clustering and dimensionality reduction
- Time-series analysis and forecasting
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Anomaly detection and change-point detection
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Experience with model evaluation, validation methods, and performance metrics
Programming & Data Analysis
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Strong programming skills in Python and familiarity with ML libraries NumPy, pandas, SciPy, scikit-learn
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Strong SQL skills for large-scale data analysis
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Ability to write clean, maintainable, and testable code
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Experien