Lead Analyst, Operations Technology Analytics
Operations Technology Analytics is a new team focused on understanding and optimizing user interactions with our Operations Technology tools and technologies. Operations Analytics is responsible for integrating analytics into the DNA of these growing tech teams, unlocking the insights that will guide the business in our quest for cost efficient, perfect orders, at scale. We bring a multidisciplinary blend of analytical experience, strong technical capability, business strategy and stakeholder management. Moreover, we’re a highly collaborative, supportive team that values learning, psychological safety and intentional career development.
What You'll Do
- Develop the strategic analytic agenda to unlock insights and guide the business.
- Collaborate closely with all facets of the organization including product management, engineering, and creative design to leverage data and analytics to drive decision making and accelerate profitable growth.
- Proactively monitor customer and field associate behavior with Ops Tech products to identify potential opportunities, establish root causes, and resolve issues.
- Bring your expertise in A/B testing to identify, design, execute, and analyze thoughtful experiments to make high-impact changes.
- Leveraging your modeling skills, apply data science techniques to solve ambiguous problems.
- Communicate key insights and recommendations to cross-functional executive leaders across the organization.
- Be the go-to technical and analytical expert for junior analysts on the team - individual contributor and people manager options available.
What You'll Need
- Proficient knowledge of SQL and statistical programming language(s) such as Python, R, SAS.
- Expert at conducting quantitative analyses on large and complex data sets, including ability to explain techniques to stakeholders.
- Experience with experimental test design (e.g., A/B testing; Multivariate and Multi-Armed Bandit) and statistical analysis to drive business decision making.
- Experience with data visualization software (e.g. Google Data Studio, Tableau, PowerBI); experience with Looker a plus.
- Experience working with large, unstructured data sets in a cloud environment (GCP, AWS, Azure)
- Experience applying data science techniques and partnering with business teams on agile model development.
- Prior experience proactively identifying areas where analytical efforts can produce a strong business value add and setting the analytics roadmap.
- Excellent communication and data presentation skills covering objectives, status, results, and recommendations.
- Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis.
- Bachelor’s in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.
- 4+ years’ work experience in relevant field.
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.