Senior Data Scientist

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-functional stakeholders, translating complex results into clear narratives that guide sales, product, and customer success decisions.

Requirements

• 7+ years in product analytics or applied data science.
• 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.

Nice To Have

• Operate MLOps platforms (such as MLflow, SageMaker, or Vertex AI) and data transformation tools (such as dbt or Snowflake), or demonstrate equivalent practical experience.
• Bring experience with model serving frameworks, data quality tooling, or observability platforms in a SaaS environment.
• Guide early-career team members through code review, pairing, and knowledge sharing to elevate collective team capability.

Pay

Minimum salary range: $124,000.00. Maximum salary range: $271,200.00. In addition to the base salary, Zoom has a Total Direct Compensation philosophy that includes base salary, bonus, and equity value. Starting pay is based on qualifications, experience, and location.

Schedule

This role follows a structured hybrid approach centered around offices and remote work environments.

Benefits

As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, options, and support for physical, mental, emotional, and financial health; work-life balance; and community contribution. Click Learn for more information.