Staff Data Scientist, Growth Analytics

Coupang•Mountain View, CA

30d

About The Position

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 Our Analytics team has a mission to power the growth of Coupang through data-driven insights. We are a team of creative problem solvers with a passion to deliver innovative business solutions. The team leverages big data to empower business decisions and deliver insights, metrics and tools in order to drive customer engagement, retention and business growth. As the growth engine within one of the largest and fastest growing e-commerce platforms on the planet, Coupang's analytics team offers countless ways for an ambitious data scientist to make an impact.

Requirements

Master's degree in a quantitative field - Computer Science, Mathematics, Engineering or related fields; 6+ years of work experience involving quantitative data analysis and machine learning models projects.
Programming language required including python, R, spark
Database experience with advanced SQL or SQL-like skills (Hadoop-Hive); experience researching and manipulating complex and large datasets; 6+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
Experience with state of the art ML modeling techniques and approaches
Hands-on experience training and applying models at scale.
Ability to communicate information effectively to a variety of groups at different levels.
Willingness to dig-in and understand the data and to leverage creative thinking and problem-solving skills are absolute musts.
Self-starter who takes the initiative to get things done.
Outstanding team player with a customer-back mindset

Nice To Haves

Experience with manipulating massive-scale customer and clickstream data.
Experience with causal inference and causal ML.
Experience with Hadoop or other MapReduce paradigms, and associated languages such as Pig, Hive, etc.
Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives
Experience in working on, backend and ML systems for large-scale user-facing products, and have a good understanding of how they all work.

Responsibilities

Build machine learning models, perform proof-of-concept, experiment, optimize and deploy your models into production.
Establish scalable, efficient, automated processes for data analysis, machine-learning model development, model validation and serving.
Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or marketing efforts.
Analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning models to drive customer engagement and retention.
Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business insights.
Design and analyze experiments to test new product ideas or marketing strategies. Convert the results into actionable recommendations.
Craft compelling stories; make logical recommendations; drive informed actions.
Communicate findings to senior leaders and evangelize data-driven business decisions