Senior Staff Data Scientist - SCM Autonomation

Please complete the Internal Transfer Request Form and submit it.

Pease make sure you are applying with your Coupang e-mail address. 

Coupang is the world's fastest and largest growing ecommerce company. Coupang is the largest e-commerce company in Korea, delivering millions of items, including fresh groceries, within hours to millions of people, 365 days a year. Our mission is to create a world in which customers wonder, ‘How did I ever live without Coupang?’ Korea is one of the fastest growing e-commerce markets in the world, and Coupang is a leader in this fast-growing industry.

Role overview 

As the Senior Staff Data Scientist - SCM Autonomation at Coupang, you will be a critical member of our SCM Autonomation team. SCM Autonomation team is responsible for building products, deep data science capabilities, analytical frameworks and owning processes end to end to provide world class solutions to our customers. As a part of this team, you will be responsible for developing innovative forecasting platforms, machine learning models, and system capabilities that enhance both the growth and health of our organization. The key focus of this role is on demand forecasting, a crucial input for ensuring optimal item availability. Effective forecasting is essential to balance inventory levels—avoiding excess stock, which ties up capital, and preventing stockouts, which impact customer satisfaction. This highly impactful and visible role focuses on leveraging deep data science expertise to build robust, scalable, and high-performing forecasting solutions. This role will involve building forecasting ML models addressing and solving complex business use cases aside promotion, seasonal, cyclicity, long horizon forecasting. The person is expected to understand deep data science model nuances, bring complete visibility & control on ML model architecture design, trade-offs taken and influence stakeholders around to take right prioritization decisions. The person is also expected to problem solve non-forecasting related data science use cases on supervised (classification, regression) and unsupervised (clustering, dimensionality reduction etc.) areas.

Key Responsibilities

1. Design/Develop/Refine ML Models and Roadmap: Develop and maintain forecasting models across various business lines such as Fresh and Core categories.
2. Feature Engineering: Perform in-depth feature engineering, incorporating both technical and domain-specific nuances to enhance model performance by creating features for various horizontal use cases like promotion, seasonality, and vertical-specific features (shelf life for Fresh, color/size for Fashion etc.)
3. Data Patching Algorithms: Detect, Design, and Implement algorithms for missing, anomalous and irrelevant data.
4. Supervised and Unsupervised problems: Solve non-forecasting related data science problems involving classification, regression, and clustering within in-stock domain (Ex: likelihood of new selection sales potential, developing product attribute vectors, price elasticity, complements/substitute items etc.)
5. Cross-functional Collaboration: Diligently work with up/downstream product, business, finance, and product analytics teams to prioritize features and integrate data science solutions effectively.
6. Model Explainability and Debugging: Provide deep insights into model design/predictions and pinpoint error analysis to resolve fundamental flaws.
7. Improving Model Lifecycle: Enhance data quality, visibility, and transparency in model inputs, institutionalize processes for validating/certifying model accuracy and integrate deep analytics into model operations to ensure ongoing refinement and robustness.

Qualifications

1. Advanced degree (Ph.D. or Master’s) in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2. 10+ years of data science or related field experience in SCM domain with proven experience in building highly analytical ML models from scratch having a focus on scalability and performance.
3. Strong knowledge of machine learning techniques, statistical analysis, and predictive modeling.
4. Expertise in data exploration, modeling, analytics and programming skills using SQL, Python, R, or equivalent languages and with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP). 
5. Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
6. Ability to create comprehensive documentation, illustrations, and simulations to drive data-driven decisions.
7. Exceptional ability to prioritize tasks ruthlessly and manage multiple projects running in parallel, ensuring timely delivery and quality.

Preferred Qualifications

• Passion for innovation and staying ahead in a fast-paced industry.
• Strong problem-solving skills and the ability to tackle complex challenges.
• Commitment to delivering world-class data science solutions that drive business success.