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Wayfair Staff Data Scientist - Machine Learning, Search & Recommendations (Search Guidance) in Boston, Massachusetts

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

<p><span style="font-weight: 400;">Wayfair Data Science powers automation &amp; decision support across all Wayfair business units. Our algorithms tackle a varied &amp; broad spectrum of challenges in the Wayfair marketplace; from empowering suppliers to easily add products to our catalog, to enabling our customers to discover and purchase a vast &amp; diverse assortment of home goods.&nbsp;</span></p>

<p><span style="font-weight: 400;">The Data Science Search &amp; Recommendations team is looking for a Staff Data Scientist to deliver state-of-the-art product search solutions. In this role, you’ll work with a group of talented data scientists, and partner with fellow engineers, analysts, and product managers to bring to life our next generation deep learning search guidance products, such as search autocomplete. You’ll test and explore state-of-the-art deep learning techniques on terabytes of data. You’ll explore how to evaluate the search guidance models both offline and online. You’ll scale solutions to serve billions of searches each day, invent solutions to keep the models up-to-date with newly added products and trendy search languages, and think about how to wrangle with real-time inference constraints. The models you develop will have tremendous business impact, directly measurable through our online A/B test platform.&nbsp;</span></p>


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


<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;">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;">Provide a strong partnership with business and engineering teams</span></li>



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


<li style="font-weight: 400;"><span style="font-weight: 400;">4+ years of experience in a quantitative or technical work environment, and advanced degree (PhD) in a quantitative field (e.g. mathematics, economics, computer science, 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, learning-to-rank, NLP, etc.)</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Deep Learning in multi-modal information retrieval experience strongly preferred</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Ability to thrive in a dynamic environment where there can be degrees of ambiguity</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>