Senior Data Scientist
AI summary of the role
Senior Data Scientist building production ML systems that predict customer growth and retention signals, directly influencing revenue strategy.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Build and deploy end-to-end ML models scoring customer expansion likelihood and churn risk
- Design and maintain automated pipelines for model retraining, monitoring, and incident response
- Partner with engineering and product teams to define telemetry schemas and data contracts
- Conduct exploratory analyses and experiments to diagnose conversion changes and validate product hypotheses
What you’ll bring
- Deep proficiency in Python (including ML libraries) and SQL
- Experience building, deploying, and monitoring ML models in production
- Solid foundations in statistics, experimentation design, and causal inference
- Experience with product telemetry or event-stream data to model user behavior
Technologies
Python · SQL · MLflow · SageMaker · Vertex AI · dbt · Snowflake
About Zoom
Enterprise collaboration platform spanning video meetings, cloud phone, contact center, and agentic AI Companion, expanding from a single-product video company into a full unified-communications suite.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Immigration sponsorship is not available for this position. What you can expect You will build production machine-learning systems that predict customer growth and retention signals. You will partner across engineering, sales, and product teams using scalable MLOps practices. You will directly influence revenue strategy through automated, data-driven scoring and insights. About the Team Our team delivers predictive intelligence that drives revenue growth decisions. We collaborate across data engineering, product, and go-to-market functions. We exist to turn product usage data into actionable business outcomes. Responsibilities Building and deploying end-to-end machine learning models — from exploration through production — that score customer expansion likelihood and churn risk, directly informing revenue strategy. Designing and maintaining automated pipelines for model
More from the job description
Immigration sponsorship is not available for this position. What you can expect You will build production machine-learning systems that predict customer growth and retention signals. You will partner across engineering, sales, and product teams using scalable MLOps practices. You will directly influence revenue strategy through automated, data-driven scoring and insights. About the Team Our team delivers predictive intelligence that drives revenue growth decisions. We collaborate across data engineering, product, and go-to-market functions. We exist to turn product usage data into actionable business outcomes. Responsibilities Building and deploying end-to-end machine learning models — from exploration through production — that score customer expansion likelihood and churn risk, directly informing revenue strategy. Designing and maintaining automated pipelines for model retraining, monitoring, and incident response, ensuring prediction accuracy and system reliability at scale. Partnering with engineering and product teams to define telemetry schemas and data contracts, ensuring high-quality inputs that support longitudinal user behavior modeling. Conducting exploratory analyses and experiments to diagnose conversion changes, validate product hypotheses, and deliver actionable recommendations to senior leadership. Communicating findings and model outcomes to cross-func [... source excerpt omitted ...] e sales, product, and customer success decisions. What we’re looking for Demonstrate deep proficiency in Python (including ML libraries) and SQL for data modeling, analysis, and production model development. Show experience building, deploying, and monitoring machine learning models in production environments with real business impact. Apply solid foundations in statistics, experimentation design, and causal inference to ambiguous business problems. Exhibit experience working with product telemetry or event-stream data to model user behavior and lifecycle transitions. Communicate complex technical findings clearly to non-technical stakeholders, including senior leadership. N [... source excerpt omitted ...] l Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value. Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience. We also have a location based compensation structure; there may be a different range for candidates in this and other locations At Zoom, we offer a window of at least 5 days for you to apply because we believe in giving you every opportunity. Below is the potential closing date, just in case you want to mark it on your calendar. We look forward to receiving your application! Anticipated Position Close Date: 05/14/26 Ways of Working Our structured hybrid approach is centered
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