Senior Staff Applied Scientist (Fraud Detection Experience)
Coupang · Seattle, WA · 1 mo ago
Hybrid$159k–$324k/yrFull-time
We need to output HTML fragment with sections: h3 for headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. We need to include only sections with real specific content. We must preserve all substantive info, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. Also remove recruitment process details? The instruction says remove application instructions. Recruitment process details might be considered application instructions; we should drop them. Also remove privacy notice, EEO statements, etc.
We need to extract substantive content: company description, role overview, responsibilities (What You Will Do), basic qualifications, preferred qualifications, pay & benefits (including base pay range, description of benefits, other compensation). Also maybe "General Description of All Benefits" and "General Description of Other Compensation". Also maybe "Pay & Benefits" section.
We need to format as semantic HTML: use for section headings. Use
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must not create sections like Schedule if not present. No schedule info given. So omit Schedule.
We need to include About the role? The posting includes a company mission paragraph at start, then "Role Overview". That could be About the role. We'll make an
About the role
with prose summarizing company mission and role overview? But we must preserve all substantive info, not summarize away detail. We can include the mission paragraph as prose under About the role. Then Role Overview could be part of that or separate? Could treat Role Overview as part of About the role. But we need to not duplicate. We'll include the mission paragraph and the Role Overview description as prose under About the role.
Then Responsibilities: "What You Will Do" bullet list. We'll make Responsibilities
with - each bullet.
Then Requirements: Basic Qualifications as list? It's a list of items separated by line breaks. We'll make
Requirements
with - each.
Then Qualifications: Preferred Qualifications as list.
Then Skills? Could combine with qualifications? But we have separate Skills section maybe not needed. The posting includes expertise on classic ML algorithms etc under responsibilities; also proficiency in Python/Java etc under basic qualifications. Could treat those as skills but we already have them in requirements. We'll not create separate Skills unless there is explicit skills list. Not needed.
Benefits: we have "General Description of All Benefits" and "General Description of Other Compensation". We'll make
Benefits
with - each benefit item. Also include other compensation as part of benefits? Could be separate but we can include under Benefits.
Pay: we have base pay range description. We'll make
Pay
with prose.
We must not include boilerplate like "Recruitment Process and Others", "Privacy Notice", EEO, etc.
We must not include duplicated lines. Ensure we preserve all substantive info: company mission paragraph, role overview, responsibilities bullets, basic qualifications bullets, preferred qualifications bullets, pay description, benefits list, other compensation description.
Let's extract exact text.
Company mission paragraph:
"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."
Note there is a missing space before "Our mission". We'll keep as is.
Role Overview paragraph:
"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."
We'll keep that as prose.
Responsibilities bullets (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
Note bullet 3 says "Expertise on classic ML algorithms..." maybe it's a responsibility.
We'll keep each as - .
Basic Qualifications bullets:
- 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 bullets:
- 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.
Pay & Benefits section:
"Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.
The base pay for this position ranges from $159,000/year to $324,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills and experience.
General Description of All Benefits
Annual bonus is 0-20% of the base salary
Medical/Dental/Vision/Life, AD&D insurance
Flexible Spending Accounts (FSA) & Health Savings Account (HAS)
Long-term/Short-term Disability
Employee Assistance Program (EAP) program
401K Plan with Company Match
18-21 days of Paid Time Off (PTO) a year based on the tenure
12 Paid Holidays
Paid Parental leave
Pre-tax commuter benefits
MTV- [Free] Electric Car Charging Station
General Description of Other Compensation
“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary or wage scale."
We need to format Benefits as list items. The "General Description of All Benefits" heading is not needed as we have Benefits section; we can just list the benefits. Also include other compensation description as a paragraph maybe under Benefits or separate Other Compensation section. But we only have Benefits heading allowed; we could include other compensation as part of Benefits list? It's not a benefit per se but description. Could make a
for other compensation.
We'll create:
Pay
Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. The base pay for this position ranges from $159,000/year to $324,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills and experience.
Benefits
- Annual bonus is 0-20% of the base salary
- Medical/Dental/Vision/Life, AD&D insurance
- Flexible Spending Accounts (FSA) & Health Savings Account (HAS)
- Long-term/Short-term Disability
- Employee Assistance Program (EAP) program
- 401K Plan with Company Match
- 18-21 days of Paid Time Off (PTO) a year based on the tenure
- 12 Paid Holidays
- Paid Parental leave
- Pre-tax commuter benefits
- MTV- [Free] Electric Car Charging Station
Other Compensation: “Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary or wage scale.
We must not include headings like "General Description of All Benefits" etc.
Now About the role section: combine mission paragraph and role overview.
We'll output:
About the role
[mission paragraph]
[role overview paragraph]
Make sure to preserve punctuation and spacing.
Now Responsibilities:
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
Requirements:
Requirements
- Bachelor's degree in
for prose. We must not create sections like Schedule if not present. No schedule info given. So omit Schedule. We need to include About the role? The posting includes a company mission paragraph at start, then "Role Overview". That could be About the role. We'll make an
About the role
with prose summarizing company mission and role overview? But we must preserve all substantive info, not summarize away detail. We can include the mission paragraph as prose under About the role. Then Role Overview could be part of that or separate? Could treat Role Overview as part of About the role. But we need to not duplicate. We'll include the mission paragraph and the Role Overview description as prose under About the role. Then Responsibilities: "What You Will Do" bullet list. We'll makeResponsibilities
with- each bullet.
Then Requirements: Basic Qualifications as list? It's a list of items separated by line breaks. We'll make
Requirements
with- each.
Then Qualifications: Preferred Qualifications as list.
Then Skills? Could combine with qualifications? But we have separate Skills section maybe not needed. The posting includes expertise on classic ML algorithms etc under responsibilities; also proficiency in Python/Java etc under basic qualifications. Could treat those as skills but we already have them in requirements. We'll not create separate Skills unless there is explicit skills list. Not needed.
Benefits: we have "General Description of All Benefits" and "General Description of Other Compensation". We'll make
Benefits
with- each benefit item. Also include other compensation as part of benefits? Could be separate but we can include under Benefits.
Pay: we have base pay range description. We'll make
Pay
with prose. We must not include boilerplate like "Recruitment Process and Others", "Privacy Notice", EEO, etc. We must not include duplicated lines. Ensure we preserve all substantive info: company mission paragraph, role overview, responsibilities bullets, basic qualifications bullets, preferred qualifications bullets, pay description, benefits list, other compensation description. Let's extract exact text. Company mission paragraph: "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." Note there is a missing space before "Our mission". We'll keep as is. Role Overview paragraph: "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." We'll keep that as prose. Responsibilities bullets (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 Note bullet 3 says "Expertise on classic ML algorithms..." maybe it's a responsibility. We'll keep each as - .
Basic Qualifications bullets:
- 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 bullets:
- 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.
Pay & Benefits section:
"Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.
The base pay for this position ranges from $159,000/year to $324,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills and experience.
General Description of All Benefits
Annual bonus is 0-20% of the base salary
Medical/Dental/Vision/Life, AD&D insurance
Flexible Spending Accounts (FSA) & Health Savings Account (HAS)
Long-term/Short-term Disability
Employee Assistance Program (EAP) program
401K Plan with Company Match
18-21 days of Paid Time Off (PTO) a year based on the tenure
12 Paid Holidays
Paid Parental leave
Pre-tax commuter benefits
MTV- [Free] Electric Car Charging Station
General Description of Other Compensation
“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary or wage scale."
We need to format Benefits as list items. The "General Description of All Benefits" heading is not needed as we have Benefits section; we can just list the benefits. Also include other compensation description as a paragraph maybe under Benefits or separate Other Compensation section. But we only have Benefits heading allowed; we could include other compensation as part of Benefits list? It's not a benefit per se but description. Could make a
for other compensation. We'll create:
Pay
Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. The base pay for this position ranges from $159,000/year to $324,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills and experience.
Benefits
- Annual bonus is 0-20% of the base salary
- Medical/Dental/Vision/Life, AD&D insurance
- Flexible Spending Accounts (FSA) & Health Savings Account (HAS)
- Long-term/Short-term Disability
- Employee Assistance Program (EAP) program
- 401K Plan with Company Match
- 18-21 days of Paid Time Off (PTO) a year based on the tenure
- 12 Paid Holidays
- Paid Parental leave
- Pre-tax commuter benefits
- MTV- [Free] Electric Car Charging Station
Other Compensation: “Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary or wage scale.
We must not include headings like "General Description of All Benefits" etc. Now About the role section: combine mission paragraph and role overview. We'll output:About the role
[mission paragraph]
[role overview paragraph]
Make sure to preserve punctuation and spacing. Now Responsibilities: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
Requirements
- Bachelor's degree in
- each benefit item. Also include other compensation as part of benefits? Could be separate but we can include under Benefits.
Pay: we have base pay range description. We'll make
- each.
Then Qualifications: Preferred Qualifications as list.
Then Skills? Could combine with qualifications? But we have separate Skills section maybe not needed. The posting includes expertise on classic ML algorithms etc under responsibilities; also proficiency in Python/Java etc under basic qualifications. Could treat those as skills but we already have them in requirements. We'll not create separate Skills unless there is explicit skills list. Not needed.
Benefits: we have "General Description of All Benefits" and "General Description of Other Compensation". We'll make