Machine Learning Scientist, Wayfair

Salary not provided
SQL
AWS
Docker
Kubernetes
GCP
Python
Airflow
Azure
Spark
NumPy
Pandas
Kubeflow
Entry, Junior, Mid and Senior level
Boston
Wayfair

A global online homeware marketplace

Be an early applicant

Wayfair

A global online homeware marketplace

1001+ employees

B2CRetailLifestyleMarketplaceInterior designFurnitureHome improvementeCommerce

Be an early applicant

Salary not provided
SQL
AWS
Docker
Kubernetes
GCP
Python
Airflow
Azure
Spark
NumPy
Pandas
Kubeflow
Entry, Junior, Mid and Senior level
Boston

1001+ employees

B2CRetailLifestyleMarketplaceInterior designFurnitureHome improvementeCommerce

Company mission

To help everyone, anywhere create their feeling of home.

Role

Who you are

  • Minimum 0-1 years of experience with PhD or 3+ years of industry experience with MSc/BaSc in STEM -- engineering, computer science, economics, etc
  • Proficiency in Python or one other high-level programming language
  • The candidate must have a strong theoretical understanding and solid hands-on expertise deploying machine learning solutions into production
  • Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity
  • Intellectual curiosity and enthusiastic about continuous learning

Desirable

  • Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
  • Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)
  • Experience with Spark, Kubernetes, Docker are nice to have

What the job involves

  • Wayfair’s Search, Marketing, and Recommendations ML teams build algorithmic systems that drive our business, enhance customer experience, and improve customer loyalty powering what our customers see on and off our site at web scale
  • You will be part of a cross-functional, collaborative team driving development of world-class ML systems that drive real-world impact
  • Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers
  • Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions
  • Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services
  • Build robust monitoring, alerting, edge-case handling mechanism
  • Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?)
  • Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on

Our take

Wayfair emerged in the early era of eCommerce with a mission to revolutionize online shopping, offering customers a convenient platform to purchase goods. Today, it stands as one of the foremost global players in the online furniture delivery industry, boasting an impressive inventory of over 33 million products.

Renowned for its extensive product range and comprehensive service offerings, Wayfair distinguishes itself by providing an end-to-end customer experience, from browsing to doorstep delivery. Despite its prominence, the company faces profitability challenges attributed largely to expansion expenses. Nonetheless, its solid presence in the competitive online homeware sector solidifies its position as a key contender.

With ambitious global expansion plans, Wayfair remains committed to maintaining its leadership in the industry. As it aspires to become the ultimate destination for all home needs, its more recent ventures into physical retail represent significant strides toward this overarching goal.

Kirsty headshot

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Some candidates hear
back within 2 weeks

-14% employee growth in 12 months

Company

Company values

  • Relentless Customer Focus: Delivering an exceptional customer experience drives everything we do. We invest in understanding our customers and partners. We are all in customer service
  • Deliver Rsults With Agility: We prioritize work that drives long-term value. We execute with urgency, learn from failure, and nimbly pivot. The outcomes of our efforts are impactful, measurable results
  • Use Good Judgement: We are bold and confident, never reckless. We make reasoned, calculated decisions based on data, critical thinking, and pattern recognition
  • Build the Best Team: We lead by setting the bar high, articulating clear goals, and diving deep. We hire, develop, and leverage only the best. Our leaders continually reevaluate and strengthen their teams and do not shy away from hard decisions. We expect and demonstrate excellence
  • Collaborate Effectively: We invest in cross-functional global partnerships that maximize impact and minimize duplication. We prize collaboration in all interactions – with our teammates, stakeholders, and suppliers. We disagree, align, and commit. Effectiveness and efficiency in collaboration are required.
  • Respect Others: We earn and show respect, treating our teammates and partners with empathy and inclusion. We presume good intent while prioritizing impact. We balance confidence and candor with humility and kindness.
  • Be an Owner: We are Wayfair first. We act on what’s best for the company, ahead of team or individual goals. We spend every dollar as if it is our own. We take pride in Wayfair’s success while planning the next win. We always think long-term
  • Innovate & Improve: We are not limited by precedent. We boldly challenge the norm. We continually identify opportunities to innovate, improve, and simplify. We value incremental improvements, but we also look for game-changing breakthroughs.
  • Adapt & Grow: We value adaptability and self-reflection. We find opportunity in every change, experience, and mistake. We are committed to continuous self-improvement.

Company HQ

Prudential / St. Botolph, Boston, MA

Leadership

Niraj Shah

(Co-Founder & CEO)

Studied Engineering at Cornell University before co-founding Spinners, a Boston-based IT services company. Previously acted as Entrepreneur in Residence for Greylock and has served as CEO of Wayfair since co-founding the company in 2002.

Steven Conine

(Co-Founder)

Co-founded Spinners before working for Operations at iXL. Conine also co-founded Pillar VC in 2016.

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