Senior Data Scientist — Forecasting & Decision Science (Remote)

Calix; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Calix is seeking a hands-on Senior Data Scientist to build forecasting, simulation, and causal inference capabilities that influence planning and operations. A primary focus is accelerating Success unit outcomes—retention, expansion, adoption, and value realization—by deploying production-grade models that inform leadership decisions.

The role emphasizes end-to-end model lifecycle, collaboration with data engineering, and rigorous evaluation to deliver measurable business impact across

Qualifications

• 7+ years of experience in data science or decision science in production.
• Advanced Python skills with pandas and NumPy.
• Deep SQL proficiency with large datasets (Snowflake or similar).
• Experience building production-grade time-series forecasting systems.
• Experience with simulation models, such as Monte Carlo methods.
• Hands-on causal inference, uplift modeling, or experimentation.
• Bayesian or probabilistic methods to quantify uncertainty.
• Translate complex problems into structured mathematical or statistical models.
• Integrate models into planning workflows and decision processes.

Responsibilities

• Design and develop robust time-series forecasting models for revenue, retention, churn, expansion, adoption, and demand.
• Partner with Success leaders to identify drivers of customer outcomes and analytical needs.
• Build simulation and scenario-modeling frameworks that consider forecasts, constraints, and causal effects.
• Apply causal inference, experimentation, and uplift modeling to isolate intervention effects.
• Develop Bayesian and probabilistic models to provide decision ranges.
• Train, back-test, validate, and continuously improve models with enterprise data.
• Manage end-to-end model lifecycle: framing, features, development, deployment, monitoring, tuning.
• Collaborate with data engineering to deploy scalable models in enterprise workflows.
• Establish rigorous evaluation practices and explainability for leadership insights.
• Translate dynamics into clear scenarios, insights, and actionable recommendations.

Skills

Python

Time-series forecasting

Causal inference

Experimentation

Communication with stakeholders

Education

Master's degree or PhD in a quantitative field

Tools

Snowflake

EconML

DoWhy

Job description

Calix is seeking a hands-on Senior Data Scientist to build forecasting, simulation, and causal inference capabilities that influence planning and operations. A primary focus is accelerating Success unit outcomes—retention, expansion, adoption, and value realization—by deploying production-grade models that inform leadership decisions.

The role emphasizes end-to-end model lifecycle, collaboration with data engineering, and rigorous evaluation to deliver measurable business impact across