Bachelor's or Master's degree in computer science, statistics, mathematics, engineering, economics, or a similar quantitative field
0–2 years work experience
Working knowledge of SQL and at least one programming language, ideally Python
Desirable experience with GitHub and analytics engineering tools such as dbt
Desirable experience in deploying ML models in production environments
Comfortable in Google Sheets and a plus if you have already touched Google AppScript or any scripting for automation
Exposure to forecasting, machine learning, or experimentation is a plus, but not required
Ready to work in a fast-paced environment where priorities shift week to week
Analytical mindset: you enjoy breaking down complex problems and following the data wherever it leads
Curiosity: you ask why, and then you ask why again, until you actually understand what is going on
Builder mentality: you would rather ship a rough working tool today than a perfect one in three months
Strong communicator: you can explain a model or a finding to a warehouse supervisor, a commercial lead, and a CEO, all in language that lands
Willingness to speak up: you challenge weak assumptions, push back on bad data, and raise issues early
Discipline and consistency: your numbers are right, your code is reviewable, and your work is reproducible
Ownership: you treat the problem as yours, not as a ticket that gets handed off
Hands on attitude: you are happy to spend a morning in the warehouse or on a delivery route to understand the data you are working with
Sign in to unlock the full job
You are seeing the role preview. Sign in with a paid plan to unlock the company name, full description, responsibilities, benefits, and the apply link.