Staff, Data Scientist (Fulfillment & Transportation)

Key Skills

Java Programming, Python Programming, C++, English Proficiency, C Programming, SQL, PowerBI, Bayesian networks, Reinforcement Learning, Tableau, Apache Hive, Linear regression, R Programming, Algorithms, SPARK Programming, Large data sets, Monte Carlo Simulation, Distributed computing

Job Description

Coupang is one of the largest and fastest growing e-commerce platforms on the planet. We are on a mission to revolutionize everyday lives for our customers, employees and partners. We solve problems no one has solved before to create a world where people ask, “How did we ever live without Coupang?” Coupang is a global company with offices in Beijing, Los Angeles, Seattle, Seoul, Shanghai, and Silicon Valley.

Job Overview:

Coupang's extensive logistics system is composed of hundreds of large and small logistics nodes, and there are tens of thousands of possible connections between each node. Through this network, more than 1 billion packages are shipped to each household a year.

As a Data Scientist you will provide ad-hoc statistical analyses to reveal operational problems and identify root causes in various operation processes. You provide decision support by building machine learning and optimization models/algorithms to solve business problems with complex rules and conflicting objectives, such as labor planning, task scheduling, FC picking/stowing optimization, operational anomaly detection, transportation routing.

Key Responsibilities:

• Apply machine learning/operations research/analytical techniques to address fulfillment center business needs, improve logistics processes, help cut operation cost, and optimize customer experiences
• Define problems, develop customized algorithms/models, and perform experimentation to provide actionable insights to stakeholders
• Mine and analyze domain data to identify improvement opportunities and drive improvement of operations
• Work with other functional teams to implement algorithms/models, and monitor outcomes
• Partner with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions

Basic Qualifications:

• Masters or PhDs in Statistics, Operations Research, Computer Science or another quantitative discipline
• 3+ years of work experience in application of machine learning/OR techniques to solve practical business problems. 5+ years of professional experience in such areas is preferred.
• Programming experience in Python (preferred) /R/SQL/Spark to manipulate data, develop algorithms/models, and draw insights from large data sets
• Strong analytical and problem solving skills
• Good understanding of the underlying mathematical foundations of statistical approaches and machine learning algorithms
• Experience with exploratory data analysis, statistical analysis and testing and development of predictive / prescriptive models
• Experience in optimizing algorithms for performance in production
• Team player with a self-motivated and “CAN-DO” attitude
• Ability to learn new techniques, and meet deadlines in a fast-moving environment
• Ability to present data and its implications in a clear and concise manner

Preferred Qualifications:

• Knowledge of fulfillment center operations, logistics or supply chain management
• Interest in reading and applying academic research to business problems
• Experience formulating linear, convex, and nonlinear optimization problems
• Experience in Bayesian inference, reinforcement learning, linear relaxation and Monte Carlo simulation
• Knowledge and experience with distributed data computing tools, such as Hive, Spark
• Knowledge and experience with Java, C, C++
• Experience with data visualization tools, such as Tableau, PowerBI, etc
• Good communication skills in English, written and verbal