By applying to this position, your application is automatically considered for the range of Data Science roles we have at Wayfair. If we think you might be a fit, a recruiter will reach out to learn more about your background and discuss relevant positions in more detail.
Who we are
Our Marketing Data Science team drives development of world-class ML systems that improve our customer understanding and marketing decisions. We build innovative DS products and services that enhance our customer experience, improve customer loyalty, and ultimately grow our business. We have a modern tech stack including sophisticated capabilities around AI, data science, causal inference and personalization. Were a highly collaborative, supportive team that values learning, psychological safety and intentional career development.
What youll do
- Define and drive the science vision for a new area of model development with an ambitious charter
- Manage your teams investment across a portfolio of legacy and new model development projects
- Lead your team and cross-functional partners to solve problems in a way that makes things easier over time. Develop and deliver DS/ML solutions that drive significant impact & are designed to be extended/generalized/reused in other workflows or projects
- Research industry trends and best practices in your domain and bring that in life at Wayfair
- Work cross-functionally with Marketing, MarTech Eng, and ML Plats Eng to build scalable marketing solutions, and influence the broader orgs technology plans for improving marketing at Wayfair
- When needed, participate in meetings with Google, Facebook, Apple, etc., to understand ad vendors technical capabilities and limitations to make the right calls on our roadmaps, and influence their strategic roadmaps
- Act as SME and provide mentorship and technical guidance beyond own team on the broader DS/Eng org
Who you are
- Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization
- 5+ years of experience working as a professional data scientist, ML engineer, or software developer. Consistent track record of autonomously delivery of DS/ML projects that drive measurable business impact.
- 3+ years of experience mentoring and developing a DS or Eng team. Collaborative team player who wants to see themselves and others thrive.
- Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis; Excellent written and verbal communication
- Proficient in one or more programming languages, e.g. Python, R, Java, C++, etc.
- Experience with GCP, Airflow, and containerization (Docker)
- Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc.
- Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning
- Advanced degree (Master or PhD) in a quantitative field
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 Berlin, or in our warehouses or offices throughout the world, were 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 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, 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. 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, or genetic information.