Data Science Tech Lead, Sales

Boston, MA

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Wayfair Inc.
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Posted 2 weeks ago

Providing good customer support in a customer’s order journey through chat and phone assistance is a priority for Wayfair. The Sales Data Science team works cross-functionally across all layers of business to innovate new, data-driven ways of improving customer experience. To do this, we use a full spectrum of ML techniques to create predictive and descriptive models from observed and unobserved aspects of the customer journey. The resulting models inject intelligence at critical points in the customer journey, from arrival on-site to a phone call in our call center, to make better business decisions.

B2C-Sales Data Science works with the live-help channels in Wayfair, enabling and optimizing call and chat touchpoints. Data Science is a central team with several verticals corresponding to different functions. Sales is part of the B2B|Sales|Service vertical.

What You'll Do  

  • Build machine learning models to enable effective and efficient sales interactions (phone, chat, virtual) for Wayfair customers
  • Identify and innovate new opportunities to drive business results through data science
  • Own the full data science life cycle: scoping to prototyping, testing, deploying, measuring value and iterating
  • Partner with engineering teams (ML Engineering, Service R&D) to integrate ML products into technical platforms and deploy real-time models at large scale
  • Partner with operational teams to help guide business decisions through model outputs and findings

What You'll Need  

  • 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)
  • 4+ years of experience in computational language (R/Python/Matlab/etc) with proven recent experience in Python
  • Thorough command of general data science and machine learning techniques, good understanding of data engineering practices
  • Relevant experience designing and implementing customer-facing systems that are scalable, fast, and resilient, preferably with a strong operationalization component
  • Ability to work on cross-functional projects and manage multiple stakeholders with competing priorities
  • Good understanding of experimental techniques for the design of A/B tests to measure the impact of initiatives
  • Communication skills that can influence across organizations and at all levels
  • People management experience is a plus

About Wayfair Inc.

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.

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.

Job tags: Economics Engineering Machine Learning Matlab ML Python R Research
Job region(s): North America
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