Coupang Global LLC

Coupang Global LLC

Senior Staff Applied Scientist

Seattle, USA · Staff+

Sponsorship not specifiedDetected 10 days ago
PythonJavaAlgorithmsMachine LearningDeep LearningTensorFlowPyTorchscikit-learnSparkAirflowNLPStatisticsA/B TestingSupply ChainLogisticsCustomer SupportElectrical EngineeringEpicCommunication

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odds of building a lasting career here

40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

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Employer immigration record

from this employer's Department of Labor filings

Green-card follow-through: 90%

Of 10 labor certifications old enough to have been used, 1 expired without the employer filing the next step. Median time from filing to decision: 492 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

4 transfer filings in the last year, covering 4 workers. Median labor-condition decision: 8 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Global Operations Optimization Science and Engineering (GOOSE) is an applied science/ML org within the Global Operations Technology (GOT) team at Coupang.
  • Counterfeit sales on Coupang are distorting market competition, damaging customer trust, creating severe legal vulnerabilities, and ultimately resulting in significant financial damage.
  • Existing enforcement at Coupang is either heavily manual, or imprecise to trust for automated action.

Responsibilities

  • Design and implement end-to-end ML systems for applications such as Commerce Risk Detection, Post Purchase Experiences, Logistics Compliance, etc.
  • Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and/or MLflow, ensuring reproducibility, scalability, and operational excellence.
  • Closely collaborate with product, operations, and back-end engineers to align technical solutions with business goals and customer experience.
  • Domain knowledge in fraud detection, customer support and/or logistics
  • Drive innovation in Coupang eCommerce Operations using ML technologies.

Requirements

  • Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
  • Proficiency in Python and/or Java, with experience in building production grade ML systems

Nice to have

  • Master's or PhD in relevant technical fields
  • Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
  • Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGMB, and/or H2o.ai
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Benefits

  • Drive and own ML vision and roadmap in large/complex projects.
  • Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning
  • 8 years of professional experience in applied machine learning
  • Experience in machine learning, deep learning, and statistical modeling

Company info

  • We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.
  • We are proud to have the best of both worlds - a startup culture with the resources of a large global public company.
  • This fuels us to continue our growth and launch new services at the speed we have been since our inception.
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This listing is sourced directly from Coupang Global LLC's careers page and normalized into a canonical job model.