Data Scientist

4d4 days ago

Zoom

San Jose, US · Full-time · $98,900 – $228,700

About this role

You will build intelligent systems that turn product data into growth insights. Working with advanced modeling and automation, you will scale predictive analytics across products. Your work drives smarter decisions that accelerate customer growth and retention.

Day-to-day, you will design scalable data models and predictive systems that inform customer growth strategies. You will partner with Product and Engineering teams to ensure reliable data collection and model deployment, and build automated pipelines and monitoring frameworks to maintain model accuracy and performance.

You will join a team that delivers insights powering revenue growth, working across Product, Sales, and Engineering to turn data into action. The team helps the business understand and predict customer behavior, and you will translate analytical findings into clear recommendations for business and product decisions.

This role offers the opportunity to drive measurable impact on customer growth and retention through data science. You will work with cutting-edge tools and collaborate cross-functionally to shape product strategy and business outcomes.

Requirements

5+ years in product analytics or applied data science.
Demonstrate strong proficiency in SQL and Python for data modeling and analysis.
Apply experience building and deploying machine learning models in production environments.
Use statistical and experimental methods to analyze and interpret product performance.
Collaborate effectively with cross-functional teams to translate data insights into business impact.
Manage model lifecycle processes, including monitoring, retraining, and performance optimization.
Leverage experience with MLOps tools such as MLflow, SageMaker, or Vertex AI.
Utilize data transformation and observability tools like dbt, Snowflake, or Great Expectations.

Responsibilities

Design scalable data models and predictive systems that inform customer growth strategies.
Partner with Product and Engineering teams to ensure reliable data collection and model deployment.
Build automated pipelines and monitoring frameworks to maintain model accuracy and performance.
Translate analytical findings into clear recommendations for business and product decisions.
Ensure data quality and consistency across telemetry and analytics systems.

Benefits

Total Direct Compensation philosophy including base salary, bonus, and equity value.
Location-based compensation structure.
Structured hybrid approach centered around offices and remote work environments.
Award-winning workplace culture and commitment to delivering happiness.