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. 

Safety continues to be one of the biggest focus areas for Zoom in the coming decade. The mission of Trust and Safety is to protect users and our platform from harms like scams and harassment caused by bad actors who violate our standards and policies. There is broad cross-functional collaboration between DS and Engineering, Product Management, Operations, Data Engineering, Analysts, and more. Data Science plays a key role in driving strategic decisions within the team since data-driven understanding is critical to achieving success in this complex and dynamic space. We employ sophisticated machine learning models to catch fraud and malicious platform behavior at scale, so you’ll also work with the ML engineers on the team to support their approaches and experiments.

This role focuses on 4 key areas:

• Product success measurement: what goals should we set? How well are we progressing towards our goals? What moves our core metrics and why? What proxy metrics can help us make faster progress with directional validity and superior coverage & latency?

• Harm prioritization: where should we be investing to protect good users? How much improvement could we make via automated and manual defense systems? 

• System maturity: how can we reduce the time from new exploits to remediation? What foundational investments will help us scale faster with higher quality? Which guardrails are most important?

• Unbiased estimation of sparse signals: with measurements of rare events, how can we keep track of what’s happening even when we only have partially observed data?

Data Scientist, Analytics - Trust and Safety Responsibilities

• Apply your expertise in quantitative analysis and data presentation to see beyond the numbers

• Monitor events through dashboards, detect anomalies, and conduct deep dive analysis on specific issues to understand their root cause

• Drive strategies and decisions via analytics

• Communicate opportunities to broad cross-functional teams and provide actionable next steps

• Partner closely with Product, Engineering, Ops and other cross-functional teams to drive product direction and prioritize roadmap
   

Minimum Qualifications

• Bachelors/Masters Degree with 5+ years (or PhD with 2+ years) of experience working within an analytical role

• Experience working independently and as a member of a cross-functional team

• Experience in querying and manipulating large datasets for analysis

• Knowledge in Python and SQL

• Strategic thinker who can drive team direction

• Preferred Qualifications

• 7+ years of experience working in an analytics organization

• Experience in the integrity and trust & safety space

• Experience leading large projects in the tech industry

Preferred Qualifications

• 7+ years of experience working in an analytics organization

• Experience in the integrity and trust & safety space

• Experience leading large projects in the tech industry