Senior Machine Learning Scientist (Ads incrementality) - Tokyo

About this role

<p><strong>About Appier&nbsp;</strong></p> <p>Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit <a href="http://www.appier.com/">www.appier.com</a> for more information.</p> <p><strong>Open to overseas candidates/Visa Support</strong><br><br>This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.</p> <h4>The Impact You’ll Make at Appier</h4> <p>Appier is seeking a&nbsp;<strong data-stringify-type="bold">Senior Machine Learning Scientist</strong>&nbsp;to join our&nbsp;<strong data-stringify-type="bold">Advertising Cloud Optimization team</strong>, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.<br>In this role, you'll measure&nbsp;<strong data-stringify-type="bold">ads incrementality</strong>&nbsp;on different type of traffic, creative, users, and also improve campaign efficiency on combination having good incrementality by machine learning model and AI automation.</p> <p><strong>What You’ll Work On</strong></p> <p>&nbsp;</p> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0">Leverage scientific methods to improve&nbsp;<strong data-stringify-type="bold">ads measurement</strong>.</li> <li data-stringify-indent="0" data-stringify-border="0">Drive&nbsp;<strong data-stringify-type="bold">online experiments</strong>&nbsp;to continuously improve ads effectiveness.</li> <li data-stringify-indent="0" data-stringify-border="0">Own the project independently.</li> <li data-stringify-indent="0" data-stringify-border="0">Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.</li> </ul> <p>&nbsp;</p> <p><strong>What We’re Looking For</strong></p> <p>&nbsp;</p> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0">Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, Econometrics, or related field.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">3+ years of industry experience on causal inference, incrementality,&nbsp;</strong>marketing mix modeling or other measurement solutions on digital Ads related fields, and understand the assumption and difference across methods.</li> <li data-stringify-indent="0" data-stringify-border="0">Proficiency in&nbsp;<strong data-stringify-type="bold">Python and SQL</strong>&nbsp;experience with modern ML frameworks (PyTorch, TensorFlow, etc.).</li> <li data-stringify-indent="0" data-stringify-border="0">Strong ownership and collaboration skills.</li> </ul> <p>&nbsp;</p> <p><strong>Language</strong></p> <p>Fluent in <strong>English or Chinese.</strong></p> <p>#LI-AK1</p> <p>&nbsp;</p>