Data Scientist (Machine Learning)
About Nelo Nelo is a leading consumer fintech and e-commerce platform in Mexico, with >$500MM in annualized GMV and >$70MM in annualized revenue. Our mission is to increase the buying power of consumers in Latin America, and we are doing so by building a modern alternative to credit cards.
What this role actually needs.
Data Scientist (Machine Learning) at Nelo in New York City. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. About Nelo Nelo is a leading consumer fintech and e-commerce platform in Mexico, with >$500MM in annualized GMV and >$70MM in annualized revenue. Our mission is to increase the buying power of consumers in Latin America, and we are doing so by building a modern alternative to credit cards.
Day-to-day expectations
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- Solve the "Why," not just the "What": You will design and deploy causal inference models to drive our underwriting and portfolio management strategies. Correlation isn't enough when you're managing risk.
- Build the Core Engine: You will create and refine the algorithms for credit pricing, personalization, and ranking. Your code will directly impact the wallet of the consumer and the margin of the company.
- Own the Infrastructure: You won't just hand off a Jupyter notebook to an engineer. You will lead ML infrastructure projects, ensuring observability and operational excellence for the models you build.
What a strong candidate brings
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- You have deep theoretical roots. We are explicitly looking for candidates with a strong academic background (PhD preferred) who understand the first principles of classification, forecasting, and optimization.
- You are a builder, not just a researcher. While you love the theory, you have at least 5 years of experience applying it in a production environment. You write production-grade Python and SQL.
- You value velocity. You understand that a perfect model shipped next year is worth less than a great model shipped next week. You can balance intellectual rigor with the need to execute.
- You are happy in NYC. This is an in-office role. We believe the hardest problems are solved when smart people are in the same room with a whiteboard.
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