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Job Description
Join our Pricing team and play a crucial role in shaping Wayfairs pricing strategy! Were a science team with a mission to optimize longterm profitability by finding the perfect balance between shortterm profitability and sustainable customer growth. We do this by leveraging economic theory cuttingedge ML econometrics and live experimentation to ensure our pricing is competitive fair to our suppliers and drives customer engagement.
In this role youll be pushing the boundaries of demand estimation and causal inference by working with rich highvolume customer data and ML tools. Youll use both observational and experimental methods to understand how customer short and longterm price sensitivity shifts in response to various business decisions. Partnering with our engineering team youll implement these bestinclass approaches as scalable solutions that drive impact by improving Wayfair pricing strategies.
What youll do
- Lead R&D effort to develop innovative demand estimation approaches that will extend current capabilities and develop new ML products to power our pricing.
- Understand our pricing strategy and optimization algorithm to identify what to measure and how to measure it.
- Work highly crossfunctionally with business leadership stakeholders and partner science and engineering teams to drive the integration of model outputs into companywide business decisionmaking and existing production systems.
- Developing robust solutions to infer or recover causal relationships from observational data in a way that minimizes selfselection or thirdvariable problems and reliance on experimental data.
- 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 demand estimation and causal inference techniques
- To stay ahead of the curve youll continuously research and evaluate new techniques in data science machine learning and pricing optimization.
Who you are
- PhD in Economics Statistics or other quantitative field with an emphasis on causal inference and/or structural modeling (e.g. industrial organization structural labor quantitative marketing OR).
- 2 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 bestinclass solutions to ecommerce space.
- Takes a customercentric approach to ideation and problemsolving
- Trackrecord of influencing nontechnical stakeholders on strategic direction by leveraging datadriven insights; excellent written and verbal communication.
- Strategic thinker with a customercentric 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
- Nicetohaves:
- 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 Youll 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
- Global Pod Outings
- Work/Life Balance:
- Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments
An Important Note about Wayfairs InOffice Policy:
All Torontobased interns coops and corporate employees will work inoffice on a hybrid schedule. Teams are in office on designated days (TuesdayThursday) and work remotely on Monday and Friday.
About Wayfair Inc.
Wayfair is one of the worlds largest online destinations for the home. Whether you work in our global headquarters in Boston or in our warehouses or offices throughout the world were reinventing the way people shop for their homes. Through our commitment to industryleading technology and creative problemsolving we are confident that Wayfair will be home to the most rewarding work of your career. If youre looking for rapid growth constant learning and dynamic challenges then youll find that amazing career opportunities are knocking.
No matter who you are Wayfair is a place you can call home. Were a community of innovators risktakers and trailblazers who celebrate our differences and know that our unique perspectives make us stronger smarter and wellpositioned 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. Thats why were 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 genetic information or any other legally protected characteristic.
Your personal data is processed in accordance with our Candidate Privacy Notice ( If you have any questions or wish to exercise your rights under applicable privacy and data protection laws please contact us at.
Employment Type
Full Time
