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Wayfair Staff Machine Learning Engineer ,Ads in Boston, Massachusetts

<p><strong>Who We Are</strong></p>

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<p><span style="font-weight: 400;">Wayfair’s Recommendations team provides the core platforms and services that allow our customers to discover and buy the products they love by serving the right content to every customer on every touchpoint. It also allows our suppliers to surface their products to the right customer to showcase their inventory and build their brand.</span></p>

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<p><span style="font-weight: 400;">The Product Recommendations team is searching for an experienced Data Science/Machine learning technical leader to join our sort optimization team. This team works on multi-objective optimizations which strike the balance of showing popular products and showcasing sponsored products or brand-aware display ads in the product search and recommendations. In this role, you’ll manage a group of talented data scientists, and partner with fellow engineers, analysts, and product managers to bring our next generation recommendation platform to life.&nbsp; The ideal candidate enjoys sitting at the boundary of data science and engineering, and is comfortable working with partners across the organization to distill ambiguous business asks into technical plans. This is an exciting opportunity to join a growing team with a tangible impact on the performance of Wayfair overall. You will directly impact and drive forward key business initiatives. Above all, you’ll get to work on problems that are both intellectually-challenging and drive real, measurable impact through our online A/B test platform, first and foremost, for our customers - and as a result for Wayfair at large.&nbsp;</span></p>

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<p><strong>What You’ll Do&nbsp;</strong></p>

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<li style="font-weight: 400;"><span style="font-weight: 400;">Own the full Data Science life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Develop quantitative models, leveraging machine learning and advanced data analysis techniques</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Architect and build technical platforms for our algorithmic engines to run at scale</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Manage a small team of experienced data scientists and machine-learning engineers to execute on a research and implementation agenda</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Uncover deep insights hidden in our vast repository of raw data, and provide tactical guidance on how act on findings</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Collaborate closely with Product, Analytics, and Engineering partners to translate business asks into technical solutions</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;">4+ years of experience in a quantitative or technical work environment, and advanced degree in a quantitative field (e.g. computer science, mathematics, economics, engineering, physics, neuroscience, operations research, etc.)</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Intuitive sense of how quantitative and technical work aligns closely with business priorities and business value</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">High comfort level with Python (preferred), or with other languages such as R, Java, C#, etc.,</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Machine Learning experience (such as supervised/unsupervised learning, deep learning, NLP, etc.)&nbsp;</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with advertising systems or multi objective optimization problems is strongly preferred</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Bonus points for intellectual curiosity and a strong desire to always be learning!</span></li>

</ul><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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