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Staff Data ScientistCalix • New York, New York, United States
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Staff Data Scientist

Calix
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Postuler Maintenant

À propos

Company Overview The Calix platform enables Communication Service Providers (CSPs) of all sizes to transform and future‑prove 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 are at the forefront of a once‑in‑a‑generation change in the broadband industry. 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. This role is ideal for PhD candidates with a minimum of 5 years of experience who want to translate research into production‑grade AI capabilities embedded directly into Calix Cloud products. Key Responsibilities 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. 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. Required Qualifications & Technical Skills PhD in Data Science or Computer Science. 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, classification, clustering, 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. Experience writing clean, maintainable, and testable code. Experience with data preprocessing, feature engineering, and exploratory data analysis (EDA). Experience analyzing broadband network and service telemetry, including metrics such as latency, throughput, packet loss, utilization, and device‑level signals. Ability to reason about data across devices, subscribers, locations, and time windows. Strong problem‑solving skills and the ability to translate ambiguous problems into analytical solutions. Clear written and verbal communication skills. Experience presenting insights through charts, dashboards, and reports. Preferred Qualifications Experience or research in broadband access networks, subscriber analytics, or network intelligence. Familiarity with Calix‑relevant broadband technologies such as Fiber (PON), Cable (DOCSIS), and Wi‑Fi telemetry. Experience with cloud‑native data platforms (AWS, GCP, Azure) and ML deployment frameworks. Exposure to MLOps practices, including CI/CD, model monitoring, and lifecycle management. Knowledge of real‑time analytics, streaming data, or large‑scale data ecosystems. Publications or applied research in network analytics, anomaly detection, forecasting, or machine learning. Compensation Base pay range varies by location: - San Francisco Bay Area: 156,400–265,700USD per year - All other U.S. locations: 136,000–231,000USD per year Additional compensation may include a bonus. Detailed information will be shared during the recruitment process.
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  • New York, New York, United States

Compétences linguistiques

  • English
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