Zoomies help the world connect — and deliver happiness while doing it. We set out to build the best video conferencing product for the enterprise, and today help people communicate better with products like Zoom Phone, Zoom Rooms, Zoom Video Webinars, Zoom Apps, and OnZoom.
We’re problem-solvers and self-starters, working at a fast pace to design solutions with our customers and users in mind. Here, you’ll work across teams to dig deep into impactful projects that are changing the way people communicate, and enjoy opportunities to advance your career in a diverse, inclusive environment.
Zoom is an award-winning workplace. We have been recognized by Comparably as #1 CEO, Company Happiness, Benefits, Compensation, Diversity, and more! Not to mention we’ve been awarded by Glassdoor as the 2nd Best US workplace & Best Large Company US CEO in 2018, Wealthfront, and Business Insider. Our culture focuses on delivering happiness, our commitment to transparency, and the tangible benefits we provide our employees and our customers.
The Data Science team lies at the foundation of Zoom’s success - you'll be working cross-functionally with teams of engineers, scientists, marketers, and product professionals on some of the most critical projects in the company - whether it's exploratory research to predict user behavior, or running experiments to optimize untapped areas of growth, or developing machine learning models that deliver “happiness” to our users more consistently and at scale. If you are passionate about data engineering and looking to join a fun and fast-moving team, we’d love to meet you! Our team is taking Zoom's data culture to the next level by integrating predictive models into our infrastructure, and we are looking for someone like you to help us get there! This role is based in Pittsburgh, Denver or Phoenix.
- Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.
- Interacts with product and service teams to identify questions and issues for data analysis and experiments.
- Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
- Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
- Having wide-ranging experience, uses professional concepts and company objectives to resolve complex issues in creative and effective ways.
- Some barriers to entry exist at this level (e.g., dept/peer review). Works on complex issues where analysis of situations or data requires an in-depth evaluation of variable factors.
- Exercises judgment in selecting methods, techniques and evaluation criteria for obtaining results.
- Networks with key contacts outside own area of expertise.
- Determines methods and procedures on new assignments and may coordinate activities of other personnel (Team Lead).
- Typically requires a minimum of 8 years of related experience with a Bachelor’s degree; or a Master’s degree plus 6 years experience; or a PhD with 3 years experience; or equivalent experience.
- Relevant software engineering experience (Python, Scala and Java) in a data-focused role
- Technical leadership in solving complex data-driven problems
- Passion for creating data infrastructure technologies from scratch using the right tools for the job
- A knack for writing, clean, readable, maintainable code
- Comfort with open source technologies like Kafka, Hadoop, Hive, Presto, and Spark
- Expertise in building out data pipelines, efficient ETL design, implementation, and maintenance
- Experience with AWS tools
- Exercises judgment within defined procedures and practices to determine appropriate action.
- Builds productive internal/external working relationships.
- Normally receives general instructions on routine work, detailed instructions on new projects or assignments.