Senior Staff Applied Scientist

Coupang•Seattle, WA

1d•$159,000 - $324,000

About The Position

Global Operations Optimization Science and Engineering (GOOSE) is an applied science/ML org within the Global Operations Technology (GOT) team at Coupang. The team builds and operates ML/optimization systems across a wide range of business operations, including supply chain, fulfillment, logistics, delivery, commerce risk detection, and post-purchase experiences. 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. To tackle this problem, this role in GOOSE will help our stakeholders in commerce risk detection to build an intelligent and comprehensive counterfeit detection system at scale.

Requirements

Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
8 years of professional experience in applied machine learning
Experience in machine learning, deep learning, and statistical modeling
Proficiency in Python and/or Java, with experience in building production grade ML systems

Nice To Haves

Master’s or PhD in relevant technical fields
Domain knowledge in fraud detection, customer support and/or logistics
Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
Demonstrated ability to work independently and manage ambiguity in fast-paced environments
Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGMB, and/or H2o.ai
Experience with ML lifecycle tools such as Airflow, MLflow, Kubeflow, and/or Amazon SageMaker.

Responsibilities

Design and implement end-to-end ML systems for applications such as Commerce Risk Detection, Post Purchase Experiences, Logistics Compliance, etc.
Formulate real-world business problems as ML problems.
Expertise on classic ML algorithms, transformer-based models, neural net modes, etc.
Drive innovation in Coupang eCommerce Operations using ML technologies.
Drive and own ML vision and roadmap in large/complex projects.
Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and/or MLflow, ensuring reproducibility, scalability, and operational excellence.
Define and track key performance metrics to evaluate model impact and identify high-leverage opportunities for improvement.
Closely collaborate with product, operations, and back-end engineers to align technical solutions with business goals and customer experience.
Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning