Applied Scientist

🏢 Twitch · 📍 San Francisco, CA 💰 $171,600 - $171,600 / yr

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Position Summary & Responsibilities

About Us

Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.

About the Role

We are looking for an Applied Scientist to solve challenging and open-ended problems in the domain of Creators and content contextual signals. As an Applied Scientist on Twitch's GTM Science team, you will use applied machine learning to tackle ambiguous business problems across problem areas such as Ads, Brand Safety, Creator Sponsorship and Content Understanding. You will lead high profile projects where you will use a wide toolbox of ML tools to handle multiple types of data, including user behavior, metadata, and user generated content such as text and video. You will collaborate with a team of passionate scientists, engineers, and product stakeholders to develop these models, prototype and put them into production, where they can help Twitch's creators and viewers succeed and build communities.

You will report to our Senior Data Science Manager for GTM. This position is located in San Francisco, CA.

You Will:

Build machine learning products to enrich Twitch’s content understanding and help creat

🎯 Candidate Preparation Guide For Twitch Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Twitch assesses deep cultural alignment with creator-first community dynamics, massive scale systems engineering, and rapid product iteration.

📋 Preparation Priorities (Key Areas to Clarify):

1. Treating the platform like traditional broadcast media or static social networks
2. Failing to prioritize creator and viewer sentiment in product decisions
3. Giving generic software engineering answers without considering real-time streaming constraints

✨ Recommended Role Alignment Hook:

I design low-latency, hyper-engaged digital ecosystems where creators and communities build compounding value together.

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