Senior Data Scientist

Company:
Location: Boston, MA

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Wayfair’s Measurement, Attribution, and Paid Search (MAPS) Data Science team develops machine-learning algorithms to assess and to drive business impact across a multitude of marketing channels. We partner closely with our Marketing and Engineering counterparts in order to uncover new opportunities and implement large scale solutions that help us connect with a wide range of new and returning customers.

What You'll Do

  • Develop quantitative models leveraging machine learning and advanced statistical analysis techniques
  • Own the full Data Science life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value
  • Tightly integrate and jointly optimize with more mature data science and engineering products related to paid search ad bidding, customer targeting, marketing attribution & causal testing
  • Coordinate, prepare, launch, and assess live experiments in order to measure the incremental impact of your own work and/or the work of partner teams
  • Uncover deep insights hidden in our vast repository of raw data, and provide tactical guidance on how act on findings
  • Drive adoption & utilization of your products across the organization in ways that drive real business value

What You'll Need

  • 2+ years of experience in a quantitative or technical work environment, or an advanced degree (PhD) in quantitative field (e.g. mathematics, economics, computer science, statistics, engineering, physics, neuroscience, operations research etc.)
  • Ability to effectively partner with cross-functional leads: strong communication skills, ability to synthesize conclusions for non-technical partners, and a desire to influence business decisions
  • Ability to thrive in a dynamic environment where Data Science plays a key role in shaping business & technical priorities
  • Comfort with ambiguity & drive to proactively shape the next questions to ask & steps to take to add clarity and drive business forward
  • Good intuition of how quantitative and technical work aligns closely with business priorities and business value; and ability to translate business objectives and constraints into technical problem formulations
  • Machine Learning experience in a professional or advanced academic setting (e.g., supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.)
  • Fluency in Python and SQL
  • Experience with big data tools such as Hadoop, Spark, Presto, etc.
  • Bonuses: experience with GCP, Linux, Git, Airflow; experience with visual embeddings or computer vision; expertise in statistical testing in a research or business environment

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.

*** Mention DataYoshi when applying ***

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