Immigration sponsorship is not available for this position
What You Can ExpectAs a Data Scientist on Zoom's Online business team, you'll apply machine learning and statistical modeling to understand user behavior, predict buying intent, and inform product decisions that affect how millions of people experience Zoom. Day to day, you'll build and validate predictive models, run experiments, and translate complex analytical findings into actionable recommendations for cross-functional partners. Working alongside product managers, engineers, and marketers, you'll bring analytical rigor to some of the most consequential growth decisions in the company. This role is well suited to someone who moves comfortably between exploratory analysis and production-ready models, and who finds meaning in work that directly shapes user outcomes at scale.
Responsibilities- Analyze large, complex datasets to identify trends and behavioral patterns related to buying journeys, customer intent, and user engagement across Zoom's self-serve products.
- Build and validate predictive models and machine learning algorithms supporting personalization, churn prediction, customer segmentation, and recommendation systems.
- Design and execute A/B tests, interpret results with statistical discipline, and translate findings into clear business recommendations.
- Collaborate with stakeholders across product, engineering, and marketing to understand business objectives and develop targeted analytical solutions.
- Communicate insights effectively to both technical and non-technical audiences through well-structured presentations and visualizations.
- Partner with Data Engineers on pipeline development to ensure robust, scalable data infrastructure that supports model production.
- Monitor model performance continuously and iterate on solutions to maintain accuracy and relevance as business conditions evolve.
What We're Looking For- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.
- 2+ years of hands-on experience in a data science or similar role, with a focus on building consumer-facing machine learning models.
- Proficiency in Python (pandas, scikit-learn, numpy) and strong SQL skills for querying and manipulating large-scale datasets.
- Experience with A/B testing, customer segmentation, LTV prediction, or personalization models in a product or e-commerce context.
- Familiarity with data visualization tools such as Tableau, Power BI, or Python libraries (matplotlib, seaborn, plotly).
- Strong problem-solving and communication skills, with comfort navigating ambiguity and translating analytical findings for diverse audiences.
- Exposure to cloud platforms (AWS, GCP, or Azure) or tools such as dbt, Databricks, Airflow, or MLflow is a plus.
Salary Range or On Target Earnings:$87,600.00 - $186,000.00
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 & 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:
10/28/26
Ways of WorkingOur 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.
BenefitsAs 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 their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click Learn for more information.
