Data Scientist (Machine Learning)

Nelo; New York (NY); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Significant equity

Medical, dental & vision insurance

Unlimited PTO

401(k)

Extended maternity and paternity leave

Relocation support

Sabbatical program

Job summary

A consumer fintech and e-commerce platform is seeking an experienced Data Scientist who will design and deploy causal inference models to enhance underwriting strategies. The ideal candidate has a PhD and at least 5 years of practical experience in Python and SQL. Responsibilities include developing algorithms for credit pricing and leading machine learning infrastructure projects. This in-office position in NYC offers significant equity, comprehensive insurance coverage, and unlimited PTO.

Qualifications

• Strong academic background in statistics and machine learning.
• At least 5 years of experience in a production environment.
• Ability to design causal inference models.

Responsibilities

• Design and deploy causal inference models for underwriting.
• Create algorithms for credit pricing and personalization.
• Lead ML infrastructure projects for model deployment.

Skills

Statistical theory

Causal inference

Python

SQL

Machine learning

Education

PhD in a relevant field

Tools

Jupyter

Job description

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.

Nelo has raised over $40M of venture capital from investors including Homebrew, Two Sigma Ventures and Susa Ventures. Nelo has additionally raised a $100M asset credit facility from Victory Park Capital.

Our lean team includes experienced leaders from top technology companies including Uber, Amazon, Rappi, and DiDi. We pride ourselves on our velocity, intellectual rigor, and efficiency. Nelo has offices in Mexico City and New York City.

Why this Role is Different

Most Data Science roles currently on the market are focused on optimizing ad clicks or slightly improving recommendation engines.

This isn\'t that.

At Nelo, your models are the product. You are building the decision engine that determines who gets access to credit in an emerging market. This involves high-stakes constrained optimization problems where "good enough" mathematics will result in direct financial loss.

We are looking for the type of person who is frustrated by the "black box" approach of modern libraries and actually understands the statistical theory and causality behind the code. If you want to apply academic-level rigor to a P&L that is scaling rapidly, this is your seat.

What You'll Do:

• 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.

Who You Are:

• 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.

What\'s on the Table

• Significant Equity (You’re building the company, you should own it).

• 100% medical, dental & vision insurance coverage for you (50% for dependents).

• Unlimited PTO (that we actually expect you to take).

• 401(k).

• Extended maternity and paternity leave.

• Relocation support and Sabbatical program.

About the Process

We know you\'re busy, so we don\'t do 8-stage interviews.

1. Quick chat with the Hiring Manager to align on expectations.

2. A business case/technical assessment (relevant to the actual job).

3. Onsite interview in NYC to meet the team.

4. Offer.

This isn’t a job for someone who wants to hide in the back office; it’s for someone who wants their math to move the market.