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 tnering 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’re looking for7+ 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, Sage Maker, 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:$Maximum:$

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 & 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:10/09/26

Ways of Working Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

Benefits As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain…