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Amazon Applied Scientist II 
United States, New York, New York 
174942293

10.06.2024
DESCRIPTION

About TwitchAbout the PositionWe are looking for applied scientists to solve challenging and open-ended problems in the domain of user and content safety. As an applied scientist on Twitch's Community team, you will use machine learning to develop data products tackling problems such as harassment, spam, and illegal content. 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 and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities.You will report to an Applied Science Manager. This position can be located in San Francisco, CA; Seattle, WA; and New York, NY.You Will- Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content.

BASIC QUALIFICATIONS

- PhD / MSc Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or similar quantitative field OR equivalent hands on experience. We welcome applicants with non-traditional backgrounds (e.g. bootcamps).
- Hands-on experience with predictive modeling and analysis to solve real-world problems.
- 2+ years of experience building models for NLP, deep learning, bot detection, anomaly detection or in another practical ML domain.
- 2+ years of experience in Python; basic proficiency with SQL.


PREFERRED QUALIFICATIONS

- PhD with a specialization in Machine Learning.
- Experience shipping your models to production.
- Familiarity with AWS or similar cloud-computing services.
- 1+ years of experience working in the safety or fraud prevention domain (not necessarily as a scientist).
- Familiarity with Twitch, its business, and its community.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.