Job description
Merchandising Data Science Integrations
Are you looking to join a team that is developing truly cutting-edge capabilities? Are you excited about the opportunity to unlock the power of Big Data’ assets? Would you enjoy being part of developing a first of its kind linkage between every day process and data science to automate merchandising related tasks? The Merchandising Data Science Integration team focuses on optimizing Wayfair’s merchandising processes by defining a problem, building enablement of data science models to be integrated into workflows and continuously optimizing to perfection. This cross-functional and entrepreneurial team sets out to manage end to end oversight beginning with defining and enabling data source availability, partnership with data science to build predictions, collaboration with analytics to assess performance and accuracy, ending with real-time services to plug-and-play into work streams.
What You’ll Do
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- Develop innovative analytical methodologies to answer strategic business questions across the organization
- Collaborate closely with data scientists and engineers to develop processes and productionize visualizations
- Partner with key stakeholders to understand strategic knowledge gaps, and develop innovative solutions to generate new processes and insights
- Work closely with the team manager(s) to develop and follow project roadmaps, including key activities, stakeholder engagement, and milestones
- Contribute innovative and strategic ideas to help shape a relatively new team, and continue to drive impact across the organization
What You’ll Need
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- Bachelor’s degree with a distinguished academic record, ideally in a quantitative field (math, economics, statistics, physics, engineering, etc.)
- Strong quantitative skills; Demonstrated ability to develop analytical methodologies and assumptions, use data to conduct the analyses, and synthesize findings
- Process-oriented with strong organizational and communication skills
- Intellectually curious, high energy, and strong work ethic; passionate about working with, normalizing, and synthesizing large amounts of data into actionable insights
- Ability to identify and succinctly summarize roadblocks and constraints, propose potential solutions, and drive towards resolution
- Attentive to detail with strong quality control
- 1+ years of work experience at a consulting firm or technology startup in an analytical and/or client-facing role
- SQL familiarity a plus, including motivation to learn and develop the skill-set
About Us
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.
Seniority Level
Entry level
Industry
- Internet
Employment Type
Full-time
Job Functions
- Engineering
- Information Technology
More Information
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1