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.

What we are looking for

• 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.

Salary Range or On Target Earnings

Minimum: $124,000.00

Maximum: $271,200.00

In addition to the base salary and/or OTE listed Zoom has a total 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 and experience.

We also have a location based compensation structure; there may be a different range for candidates in this and other locations.

Anticipated Position Close Date

07/28/26

EEO Statement

We believe that the unique contributions of all Zoomies is the driver of our success. To make sure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Zoom is proud to be an equal opportunity workplace and is an affirmative action employer. All your information will be kept confidential according to EEO guidelines.