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Wayfair Data Science Tech Lead, Embeddings in Boston, Massachusetts

<p><span style="font-weight: 400;">The Marketing Data Science team at Wayfair develops machine learning models and reinforcement learning systems to power algorithmic decision-making across paid and owned media and marketing channels, including Paid Search, Display &amp; Social Ads, Direct Mail, Email Marketing and Push Notifications.</span></p>

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<p><span style="font-weight: 400;">In this role, you will leverage massive amounts of data to solve complex business problems focused on enhancing the customer experience and driving long-term value. You will be processing petabytes of first party and third party clickstream data to build customer-centric ML models. These models ultimately plug into our ecosystem of algorithmic decision-optimization systems and power millions customer-level decisions each day. Depending on your specific pod, these predictions or decisions could range from: What do we think she needs? What’s her stylistic preference? Should we show her an ad? On what channels? How frequently? How much do we bid? Which creative asset speaks to her uniqueness? etc.</span></p>

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<p><span style="font-weight: 400;">Above all, you’ll get to work on problems that are both intellectually-challenging and drive real, measurable impact, first and foremost, for our customers - and as a result for Wayfair at large. To get a better sense of the type of projects we work on, check out our Data Science &amp; Machine Learning blog posts </span><a href="https://tech.wayfair.com/category/data-science/"><span style="font-weight: 400;">here</span></a><span style="font-weight: 400;">!</span></p>

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<p><strong>What You'll Do</strong></p>

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<li style="font-weight: 400;"><span style="font-weight: 400;">Partner closely with peer data scientists and ML engineers to build highly scalable modeling approaches and deploy model outputs into existing production systems.</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Train deep-learning models for representation learning, capturing what makes customers unique and enhancing customer-level personalization.&nbsp;</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Wrangle and process petabytes of data from various data sources.</span></li>

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<li style="font-weight: 400;"><span style="font-weight: 400;">You’ll be a builder of tools, software, and microservices that enhance or streamline various steps or challenges within the data science workflow &amp; our tech stack.</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.</span></li>

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<p><strong>What You'll Need</strong></p>

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<li style="font-weight: 400;"><span style="font-weight: 400;">BSc in computer science and 4+ years of experience in data engineering, data science, or software development,</span><em><span style="font-weight: 400;"> or </span></em><span style="font-weight: 400;">PhD or MS in computer science and 3+ years experience in data engineering, data science, or software development</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Proficient in parallel computing and big data technologies, particularly Hadoop, Hive, Spark.</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Commercial experience training and productionizing deep learning models, and in production-environment-driven ML design.&nbsp;</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Proficient at one or more programming languages, e.g. Python, R, Java, C++, etc.</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Comfortable with SQL and ability to wrangle data from various sources</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Action-oriented, autonomous individual with a bias towards solving problems from a customer-centric lens</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">A knack for finding the right degree of pragmatism and delivering solutions in a iterative manner, adding only as much complexity as needed in each step along the way</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">A curious mind open to continuous learning and motivated to autonomously drive projects and thrive in a dynamic environment where there can be ambiguity</span></li>

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<p><br><br></p><div class="content-conclusion"><p><strong>About Wayfair Inc.</strong></p>

<p>Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.</p>

<p>No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.</p></div>

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