Location: Boston or Seattle

 

Who we are

Our Long Term Impact (LTI) Science team drives development of world-class Machine Learning systems that estimate the long term impact of business decisions and customer actions. We build innovative ML products and services that provide insights to drive LT-aware decisions that improve our customer experience and loyalty in the long term, and ultimately grow our business. We have a modern tech stack including sophisticated capabilities around causal inference and Machine Learning. We’re a highly collaborative, supportive team that values learning, psychological safety and intentional career development.

 

As a senior ML Scientist, you'll be working to push the boundary of approaches to causal inference with rich, high-volume customer data, identifying drivers of business growth beyond A/B testing. With engineering partners you'll implement these best-in-class approaches as scalable solutions to drive broad impact across marketing, operations, and storefront. This role is an opportunity to lead how Wayfair approaches work at the intersection of data engineering and statistics. 

 

What you’ll do

• Lead R&D effort to develop innovative causal inference approaches that will extend current capabilities and develop new ML products to provide insights on LTI.
• Work highly cross-functionally with business leadership, stakeholders, and partner science and engineering teams to drive the integration of model outputs into company-wide business decision-making and existing production systems. 
• Developing robust solutions to infer or recover causal relationships from observational data, in a way that minimizes self-selection or third-variable problems. 
• Develop and own communication strategy for both technical and business stakeholders (including executive documentation and progress updates)
• Act as a subject matter expert and thought leader on causal inference techniques; research industry trends and best practices and bring them to life at Wayfair. 
• Provide mentorship and technical guidance to develop your team as well to influence broader science organization.

 

Who you are

 

• PhD in Economics, Statistics or other quantitative field with an emphasis on causal inference.
• 3 years of experience working as a professional ML or research scientist in causal inference. Consistent track record of autonomous delivery of DS/ML projects that drive measurable business impact. 
• Collaborative team player who wants to see themselves and others thrive. 
• Expertise in causal inference and interest in bringing best-in-class solutions to e-commerce space. 
• Takes a customer-centric approach to ideation and problem-solving
• Track-record of influencing non-technical stakeholders on strategic direction by leveraging data-driven insights; excellent written and verbal communication.
• Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization
• Strong SQL skills and excellent software engineering skills in Python
• Nice-to-haves:
• Experience with GCP (BigQuery, GCS, Dataproc, Notebooks), Airflow, and containerization (Docker)
• Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, Spark, etc.

Why You’ll Love Wayfair:

• Time Off:
• Paid Holidays
• Paid Time Off (PTO)
• Health & Wellness:
• Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
• Life Insurance
• Disability Protection (Short Term & Long Term Disability) 
• Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
• Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
• Caregiver Services
• Financial Growth & Security:
• 401K Matching (Employee Matching Program)
• Tuition Reimbursement 
• Financial Health Education (Knowledge of Financial Education - KOFE)
• Tax Advantaged Accounts
• Family Support:
• Family Planning Support
• Parental Leave
• Global Surrogacy & Adoption Policy
• Professional Development & Recognition:
• Rewards & Recognition 
• Global Employee Anniversary Awards 
• Paid Volunteer Work 
• Unique Perks:
• Employee Discount 
• U.S. Bluebikes Membership
• Global Pod Outings
• Work/Life Balance:
• Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments