Tech Lead L3 Data Scientist
At Wayfair, data drives all of our business decisions. The Data Science Marketing team develops machine learning models and reinforcement learning systems to power algorithmic decision-making across paid and owned media and marketing channels, including Paid Search, Display & Social Ads, Direct Mail, Email Marketing, and Push Notifications, etc. These channels drive millions of site visits and billions of dollars of revenue to our business.
We are looking for an experienced data scientist to join the Paid Search Data Science team. In this role, key responsibilities will be to develop scalable algorithms and platforms that optimize our Paid Search bidding strategies. As a tech lead, you will work closely with other data scientists, as well as members of our internal Marketing and Engineering teams, to apply data science and machine learning skills to solve one of our most impactful and intellectually challenging data science problems at Wayfair.
What You'll Do
- Responsible for the design and implementation of core components of our Paid Search bidding platform which supports one of the biggest marketing channels at Wayfair
- Work towards scaling up an already large base of tens of millions of keywords and SKUs being bid on a daily and weekly basis
- Develop quantitative models, leveraging machine learning and advanced data analysis techniques to optimize our bids to achieve specific business objectives
- This includes problem definition, data acquisition, data exploration and visualization, feature engineering, experimenting with ML algorithms, evaluating and comparing metrics, deploying the models and iteratively improving the solution
- Uncover deep insight hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings
- Improve the performance of predictive models through feature engineering, feature selection, tuning amongst other methods
- Architect and build technical platforms for our algorithmic engines to run at scale
- Leverage our work in order to increase adoption across our business partners, to drive real business value
- Strong partnership with business and engineering teams
What You'll Need
- 4+ years of industry experience in data science / machine learning
- Hands-on experience developing statistical models and machine learning solutions to support paid search optimization and development of keyword bidding algorithms
- Proficient at one or more programming languages, e.g. Python, R, Java, C++, etc.
- Prior experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc.
- Experience with GCP, Airflow, and containerization (Docker) are nice to have
- A bias towards solving problems from a customer-centric lens and an intuitive sense for how the work aligns closely with business objectives
- Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
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.