Data Scientist

We are looking for a Data Scientist to join the Profitability Algorithms team. We use forecasting, analytics, big data, statistics, and machine learning to coach suppliers and delight customers.

Our work touches many data science domains. We consist of: economists specializing in time series/forecasting, machine learning engineers who build predictive models (supervised and unsupervised) and robust data products for customer- and supplier-facing platforms, and business strategy partners that align our solutions with what will benefit Wayfair/customers/suppliers. We are looking for a generalist that is eager to grow in and collaborate across all of these domains.

Culturally we 

• Value respect, inclusion, collaboration, integrity, and grit.
• Make decisions based on what is long-term best for Wayfair, its customers and suppliers. Not what is short-term best or best for our team.
• Provide and seek feedback. We care personally about the team and challenge directly to ensure we always raise each others’ standards.
• Empower and sponsor colleagues.
• Stay nimble by simplifying solutions to quickly iterate upon.
• Seek different perspectives to make better decisions.
• Embrace people for who they are, what they are interested in, and their unique strengths no matter their background.
• Accomplish a large amount of high impact work.

What You'll Do

• Build models around various cost components, powering several margin aware initiatives throughout the company
• Balance predictive accuracy with explainable and interpretable estimates for supplier facing programs
• Scope concrete data science solutions to ambiguous business problems.
• Collaborate with economists, machine learning engineers, data engineers, and business stakeholders to ensure the end-to-end success of your solutions.
• Communicate the value of your work through logical, cohesive stories.
• Mentor and empower junior data scientists.

What You’ll Need

• The ability to learn fast, a willingness to work hard, integrity, grit, compassion, and a team-first attitude. 
• Genuine interest in the happiness, well-being, and success of everyone on your team.
• Ability to effectively work with business leads and data scientists: strong verbal and written communication skills, ability to synthesize conclusions for non-experts, and desire to influence business decisions
• Masters and 2+ years of experience in a quantitative or technical work environment OR PhD in quantitative field (e.g. data science, mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.)
• Proficient at one or more programming languages, e.g. Python, R, Java, C++, etc. Experience using these to build machine learning models or run econometrics.
• Prior experience building data processing pipelines. For example, with tools such as SQL, Hive, Spark, BigQuery, or Airflow.

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.