Senior Data Scientist, Data Analytics

Location: Remote - USA

Calix is building the next generation of decision intelligence capabilities across its business. The Analytics & Decision Science team is responsible for moving beyond reporting to develop predictive, causal, and simulation-driven solutions that directly influence how the company plans and operates.

We are seeking a hands-on Senior Data Scientist to build the forecasting, simulation, and causal inference capabilities needed to evaluate business strategies, quantify uncertainty, and improve leadership decision-making. A primary focus of this role will be supporting the Success business unit’s objectives, including improving customer retention, expansion, adoption, and value realization.

This role will translate complex, real-world business systems into production-grade models and decision-support tools that deliver measurable business and customer outcomes.

What You’ll Do

• Design and develop robust time-series forecasting models for critical business metrics, including revenue, retention, churn, expansion, customer adoption, and operational demand.
• Partner with Success leaders to identify the key drivers of customer outcomes and develop analytical capabilities that support the business unit’s strategic and operational objectives.
• Build simulation and scenario-modeling frameworks that integrate forecasts, business constraints, and causal effects to evaluate strategies and support decisions under uncertainty.
• Apply causal inference, experimentation, and uplift modeling to isolate and measure the impact of customer and business interventions against baseline trends.
• Develop Bayesian and probabilistic models that quantify uncertainty and provide leaders with decision ranges rather than point estimates alone.
• Use historical and current enterprise data to train, back-test, validate, and continuously improve models.
• Manage the end-to-end model lifecycle, including problem framing, feature engineering, model development, deployment, monitoring, and tuning.
• Partner with data engineering and platform teams to deploy scalable models that integrate with enterprise data systems and Success business workflows.
• Establish rigorous evaluation practices, including back-testing, sensitivity analysis, explainability, and measurement of customer and business impact.
• Translate complex customer and business dynamics into clear scenarios, insights, and recommendations aligned to leadership decision points.
• Additional Locations: Remote - Canada