Lead Data Analyst, Service Delivery Analytics Team
Customer contacts with Wayfair’s 2000+ Sales & Service agents exhibit many different traits that have an impact on Wayfair’s KPIs. The Service Delivery Analytics team plays a vital role in exploring the data they have on those traits and defining what represents a ‘Quality’ interaction, which in turn drives strategic and tactical opportunities to improve the business. You will be part of an innovative team dedicated to developing top-notch analytical talent through problem-solving and driving the business through data analysis. You will apply analytical and data modeling skills to provide insights and recommendations addressing some of Wayfair’s most important problems.
What You’ll Do
- Understand, clean, and work with data from multiple sources to conduct data analysis and build statistical models that provide meaningful conclusions. This includes data from traditional sources as well as unstructured sources such as text-based data.
- Collaborate closely with the data science team to develop processes and productionize models
- Create visualizations and dashboards to effectively communicate insights from various analyses to drive business decisions using tools such as Tableau and R
- Partner with business stakeholders to understand business process and data requirements, and to drive change within the organization based on our analysis
- Perform basic data modeling tasks and refine live models using tools such as Python and R
- Use audio transcription data to build models for various factors based on content of call (ex. Disposition codes, proxy customer satisfaction, etc.)
- Construct optimization models to weight and score the impact of generalized call behaviors which impact multiple performance metrics
- Work with stakeholders and internal data science organization to deliver data science output to field service employees in a consumable format (ex. Recommended behavior opportunities based on data science output)
What You’ll Need
- 4+ years of experience in a quantitative or technical work environment
- Advanced degree (Masters or PhD) in Mathematics, Engineering, Economics, Statistics, Physics, Computer Science or other concentrations with heavy quantitative focus
- Strong quantitative and problem solving skills to be able to analyze large, unstructured data sets, draw out insights, proactively communicate those insights and drive business decisions
- Ability to construct models using unstructured data inputs with languages such as Python or R
- Ability to thrive in a dynamic environment where there can be degrees of ambiguity
- SQL familiarity a plus, including motivation to learn and develop the skill-set
Wayfair is one of the world’s largest online destinations for the home. Whether you work in their global headquarters in Boston or Berlin, or in their warehouses or offices throughout the world, they’re reinventing the way people shop for their homes. Through their commitment to industry-leading technology and creative problem-solving, they 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. They’re a community of innovators, risk-takers, and trailblazers who celebrate their differences, and know that their unique perspectives make them stronger, smarter, and well-positioned for success. They value and rely on the collective voices of their employees, customers, community, and suppliers to help guide them as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why they’re proud to be an equal opportunity employer. They 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.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1