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Machine Learning Scientist II
Product Recommendations
Posted on 12/30/2022
Mountain View, CA, USA
Experience Level
Desired Skills
Apache Hive
Apache Spark
Data Analysis
Data Science
Natural Language Processing (NLP)
  • 2+ years experience with advanced programming languages and big data/distributed system tools like Python, R, Scala, Java, Hive, SQL, Spark, etc
  • 2+ years of professional machine learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, NLP, etc.), and familiarity with recommender systems
  • 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
  • Ability to effectively work in a dynamic environment, where there can be degrees of ambiguity, with high-level business stakeholders: strong communication skills, ability to synthesize conclusions for non-experts and a desire to influence business decisions
  • Excellent organizational, analytical, and hypothesis-driven critical thinking skills to identify business opportunities and transform data into actionable insights
  • 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)
  • MS or PhD degree in a quantitative or related field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) or equivalent work experience
  • Develop quantitative models, leveraging machine learning and advanced data analysis techniques to improve our product recommendations
  • Own the full Data Science/Machine Learning life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value
  • Coordinate, prepare, launch and assess live experiments in order to measure the incremental impact of your own work and/or the work of partner teams
  • Uncover deep insights hidden in our vast repository of raw data, and provide tactical guidance on how act on findings
  • Drive adoption and utilization of your products across the organization in ways that drive real business value
  • Architect and help define the required technical platforms that enable us to produce models at scale

5,001-10,000 employees

Online home goods retailer
Company Overview
Wayfair's mission is on a mission to help everyone, anywhere create their feeling of home. Wayfair is an online retailer that offers a wide selection of home furnishings and decor.
Company Core Values
  • Relentless customer focus
  • Deliver results with agility
  • Use good judgement
  • Build the best team
  • Collaborate effectively
  • Respect others
  • Be an owner
  • Innovate & improve
  • Adapt & grow