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Compensation expectations
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Compensation options have not been published for this role yet.
Role summary
Answer operational questions with data and put the useful ones into a decision or a model the product can run. Remote, full-time, client unnamed until interview.
What you will build
Who we are AI ScienTechs is an engineering partner. We introduce vetted Latin American engineers to U.S. companies. This page describes the work. It does not name the client. You learn the company only if you are invited to their interview. About the role You will work from a business question to a result someone can use. Sometimes that is an analysis with a recommendation. Sometimes it is a model or a score inside the product. You are responsible for the data you trusted, the method, and the limit of the claim. What you will do - Define the question, the metric, and the decision the work is meant to change. - Find, clean, and document the data. Say when the data cannot support the claim. - Build analyses, experiments, or models that a product or operations team can act on. - Validate results against reality, including segments where the average hides a failure. - Hand off anything that must run repeatedly: definition, schedule, owner, and how to know it broke. - Write the conclusion in English a non-specialist stakeholder can use. - Partner with engineers when the result has to live in production rather than in a notebook. What we look for - Years doing applied data science or analytics that changed a product or an operation. - Strength in SQL and Python, and in explaining uncertainty. - Experience taking a model or metric out of a notebook and into a recurring process. - Skepticism toward leaky features, vanity metrics, and unreproducible notebooks. - Professional English for written findings and live reviews. - A résumé with the decision your work informed, not only the algorithm name. How you join - The engagement is full-time and remote, from Latin America, with overlap on U.S. business hours. - The working language is professional English: meetings, writing, and review. - Pay is in USD. The amount is agreed with you after evaluation, before any client interview. It is not posted on this page. - We review technical depth and how you work with other people. This is not a marketplace where you bid for the seat. - Create your account and submit your résumé against this role. Your profile stays in our talent network for this opening and for later matches.
Technical requirements
- Python
- SQL
- Experimentation
Nice to have
- Machine learning
- Statistics
- Data modeling
Evaluation process
Applications are reviewed for craft and delivery fit. Compensation preference is an economic signal — selection is based on overall fit, not compensation alone.