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As a Data Scientist on the Money team at Twitch, you will focus on creator payouts, payments infrastructure, and fraud detection. You will measure and refine payout-related programs and support new monetization initiatives. This role involves analyzing policy and program changes, owning reporting and insights, partnering with stakeholders, writing and validating pipelines, and applying causal inference methods to estimate the impact of payout changes. This role is well suited for someone early on in their data science career who is eager to take ownership of high-impact, cross-functional projects.

<h3>About Us</h3> 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 <a class="c-link" href="https://link.twitch.tv/TwitchLinkedinJD" target="_blank" data-stringify-link="https://link.twitch.tv/TwitchLinkedinJD" data-sk="tooltip_parent">LinkedIn</a>&nbsp;and&nbsp;<a class="c-link" href="https://link.twitch.tv/TwitchTwitterJD" target="_blank" data-stringify-link="https://link.twitch.tv/TwitchTwitterJD" data-sk="tooltip_parent">X</a>,&nbsp; and discover the projects we’re solving on our&nbsp;<a class="c-link" href="https://link.twitch.tv/TwitchBlogJD" target="_blank" data-stringify-link="https://link.twitch.tv/TwitchBlogJD" data-sk="tooltip_parent">Blog</a>. Be sure to explore our&nbsp;<a class="c-link" href="https://link.twitch.tv/TwitchInterviewingJD" target="_blank" data-stringify-link="https://link.twitch.tv/TwitchInterviewingJD" data-sk="tooltip_parent">Interviewing Guide</a>&nbsp;to learn how to ace our interview process. <h3>About the Role</h3> We’re looking for a Data Scientist to join the Money team at Twitch, which supports the systems behind creator payouts, payments infrastructure, and fraud detection. In this role you’ll focus on Payouts. Payouts is a high-leverage area that shapes how and when creators are paid and payout eligibility.&nbsp; You’ll work closely with product, engineering, finance, legal, and data partners to measure and refine our payout-related programs like the Plus Program and support new monetization initiatives to expand who can monetize on Twitch. While many changes are policy driven rather than AB tested, they require thoughtful measurement, reporting, operations, and causal reasoning. This role is well suited for someone early on in their data science career who is eager to take ownership of high-impact, cross–functional projects and grow into a senior role. You’ll need to be comfortable&nbsp; with writing SQL, working with imperfect data, and flexing into data workflows when data engineering coverage is limited. You can work in San Francisco, CA; Irvine, CA; New York, NY; or Seattle, WA <h3>You Will:</h3> <ul> <li>Analyze and evaluate policy and program changes that affect how creators are paid</li> <li>Own reporting and insights related to payout eligibility, earning, and program performance</li> <li>Partner with cross-functional stakeholders to inform product and business decisions</li> <li>Write, maintain, and validate pipelines to support recurring analytics and reporting</li> <li>Apply causal inference methods to estimate the impact of payout changes</li> </ul> <h3>You Have:</h3> <ul> <li>1+ years of experience as a data scientist, data analyst, or a related field</li> <li>Proficiency in SQL</li> <li>Proficiency with Python or R</li> <li>Understanding of Causal Inference concepts&nbsp; (ex/ DiD, matching, IPW, experiment design)</li> <li>Strong communication skills across technical and non-technical stakeholders</li> <li>High level of comfort creating dashboards</li> </ul> <h3>Bonus Points</h3> <ul> <li>Hands-on experience with Airflow, Sagemaker or deploying ML models in production environments</li> <li>Strong familiarity with econometrics&nbsp;</li> <li>Contribute to machine learning efforts in fraud or churn prediction</li> <li>Experience Ideating, executing, and analyzing A/B tests.</li> </ul> <h3>Perks</h3> <ul> <li>Medical, Dental, Vision &amp; Disability Insurance</li> <li>401(k)</li> <li>Maternity &amp; Parental Leave</li> <li>Flexible PTO</li> <li>Amazon Employee Discount</li> </ul> &nbsp; Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.&nbsp; Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.&nbsp; Job ID: TW8811

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