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Wayfair Data Science Tech Lead, Service in Boston, Massachusetts

<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;">&nbsp;</span><span style="font-weight: 400;">Customer service is a competitive differentiator for Wayfair. The Service Data Science team builds ML products to ensure a seamless post-order customer journey. We derive insights from data sources ranging from clickstream to customer texts and call transcripts, build predictive models to make data-driven decisions at scale, and design optimization tools that help improve customer lifetime value and profitability. Our products directly impact the millions of customers that interact with Service every month and the thousands of agents that help serve that experience.&nbsp;</span></p>

<p><span style="font-weight: 400;">We are looking for a data scientist to lead the Contact Prediction workstream within Service Data Science. In addition to guiding decisions for resource allocation against service demand, this workstream will also inform strategies for contact prevention to ultimately create a more frictionless shopping experience for our customers.</span></p>

<p><strong>What You'll Do</strong><span style="font-weight: 400;">&nbsp;&nbsp;</span></p>


<li style="font-weight: 400;"><span style="font-weight: 400;">Serve as the technical lead for the Contact Prediction workstream</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Develop contact prediction models that guide optimal staffing decisions and real-time resource allocation across multiple channels&nbsp;</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Build models to understand causal relationships between various pre- and post-order on site (clickstream, order) and off-site (carrier, supply chain) events and service contacts to inform contact reduction strategies</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Own the data science life cycle from scoping to prototyping, testing, deploying, measuring value and iterating</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Partner with engineering teams (ML Engineering, Service R&amp;D) to integrate ML products into technical platforms and deploy real-time models and services</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Partner with operational teams to help guide business decisions through model outputs and findings</span></li>


<p><strong>What You'll Need </strong><span style="font-weight: 400;">&nbsp;</span></p>


<li style="font-weight: 400;"><span style="font-weight: 400;">Master’s degree in quantitative field (statistics, mathematics, economics, operations research, physics, neuroscience etc) and 4-6+ years of experience OR PhD (preferred) and 3-4+ years of experience in quantitative field (statistics, mathematics, economics, operations research, physics, neuroscience etc)</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">3+ years of experience with Python, PySpark, SQL and Google Cloud (or AWS/Azure)</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Thorough command of general data science and machine learning techniques, good understanding of data engineering practices</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Relevant experience designing and implementing customer-facing systems that are scalable, fast, and resilient, preferably with a strong operationalization component</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Ability to work on cross-functional projects and manage multiple stakeholders with competing priorities</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Good understanding of experimental techniques for the design of A/B tests to measure the impact of initiatives</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">Communication skills that can influence across organizations and at all levels</span></li>

<li style="font-weight: 400;"><span style="font-weight: 400;">People management experience is a plus</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>