Senior Staff Applied Scientist

Coupang · Seattle, USA · по договорённости

Компания
Coupang
Город
Seattle, USA
Зарплата
по договорённости
Уровень
senior
Формат
full_time
Иностранная компания
нанимает русскоязычных

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. 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. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

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.

What You Will Do

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

Basic Qualifications

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

Preferred Qualifications

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 mod

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