Staff, Data Scientist (Ads Analytics)

Coupang•Mountain View, CA

23h•$152,000 - $261,000

About The Position

The Coupang Ads Product Analytics team maximizes revenue from Coupang advertising solutions and helps our user get value from ads. We are responsible for helping drive product strategy across entire ads business. We bring data together to generate actionable insights, answer complex business questions, and help us deepen our understanding of Customers. Our focus is on Coupang’s ads business on Ecommerce, and we do this by analyzing KPI’s, analyzing the success of A/B and multivariate testing initiatives.

Requirements

Master’s Degree in Computer Science, Electrical Engineering, Math or a closely related field
4 years of Data Scientist experience in customer-facing technology companies
Expertise in experimentation and statistics
Strong SQL
Python or R for statistical analysis
Hive, Presto, Airflow
Experience with ML modeling design, deployment, and optimization
Strong statistics background
Experience in working on backend and ML systems for large-scale user-facing products
Data visualization (e.g., Tableau, Qlik, Looker, Power BI)
Excellent quantitative analysis skills
Strong presentation and communication skills
Highly organized and detail-oriented
Ability to manage multiple projects simultaneously for multiple stakeholders in a fast-paced organization

Nice To Haves

6+ years of experience as a data scientist performing ads data analysis, ML model building and optimization, financial analysis, market research, and executive reporting.
Previous experience in AdTech / Advertising (search, display, branding, retargeting, social, streaming video…), Digital Marketing, Ad Agency, or related domains.

Responsibilities

Develop and test various auction and monetization models.
Provide simulations of the possible impact of changes to be introduced on revenue.
Deliver a set of Key Performance Indicators, used for reporting on product adoption, usage, performance, and churn.
Provide visibility into the effectiveness of the group’s monetization efforts.
Design and maintain inventory and revenue forecasting models as a critical component of the revenue optimization process.
Assist with analyzing sales patterns to identify trends and aid financial forecasting.
Design, conduct, analyze and uncover insights from A/B tests to inform and prioritize product iterations.
Perform cohort studies to answer “why?” on test result drivers.
Build timely, compelling, fact-based test recaps that strongly communicate the business ‘story’ behind the data and test outcomes.