Senior Machine Learning Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Wayfair.com is a leader in the e-commerce space for all things home. Wayfair’s community of Data Scientists and Machine Learning Engineers are obsessed with using data and technology to help our customers build a home that they love. Our technology platforms support millions of searches for the perfect item every day, providing a top-of-class purchasing and delivery experience. Come help us innovate and grow to our next $10B in revenue!

We are looking for an experienced machine learning engineer interested in partnering with data scientists, product managers, software engineers, and cross-functional business partners (e.g. marketing, website, B2B, pricing, search and recommendation) to drive and expand Wayfair’s state-of-the-art customer identity products. This includes but is not limited to operationalizing and scaling advanced statistical and machine learning models to power probabilistic device, person, and household graphs at Wayfair and researching new clustering, feature engineering, and predictive modeling techniques to extract insights with more accuracy and granularity.

We’re looking for someone who not only enjoys solving ambiguous scientific problems, writing code and building ML models in production, but is also able to upskill engineers, data scientists, and business leaders around them through leading by example. In this role, you will be driving cutting-edge machine learning and statistical research to continuously improve the accuracy and robustness of probabilistic identity products, increase the recognition of and reach to Wayfair customers, increase the computational efficiency of the production pipeline, and empower the performances of various downstream products, such as personalization and recommendation services, marketing attribution, and online AB experimentation platforms.

What You'll Do

• Lead the research and development of machine learning models and pipelines to improve the accuracy and efficiency of identity recognition at Wayfair.
• Develop scalable identity products by leveraging Google Cloud native technologies. 
• Drive identity integrations & align with key stakeholders across various products and platforms.
• Work with software engineers to productionalize machine learning outputs for real-time consumption via graph database structures.
• Think outside of the current technology/stack limitations to push the boundaries on what is possible and deliver feasible solutions collaboratively.
• Promote a culture of machine learning and data science excellence by participating in weekly research, learning, and development sharing sessions.

What You'll Need

• Advanced degree (Master or PhD) in Machine Learning, Computer Science, Engineering, Statistics, or a related quantitative field. 
• 3+ years of experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale.
• Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Python, and SQL.
• Excellent organizational, analytical, and hypothesis- driven critical thinking skills to identify business opportunities and transform data into actionable insights.
• Excellent communication skills to explain complex data science and machine learning concepts/ideas/methods to technical and business audiences.

Nice to Have

• Mix of start-up and large-company experience working on data science and machine learning.
• Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks).
• Direct experience leading research around customer identification.
• Familiarity with web development, cookie usage, HTTP protocols, and consumer privacy laws.
• Experience developing and applying innovative machine learning methodologies to tackle real-world identity challenges (e.g. customer device mappings, person & household graphs) and translating technical results to business objectives and impacts..
• Experience with graph databases, such as TigerGraph.