Machine Learning Engineer - Fraud & Credit Risk (Production-Ready)

Payjoy; Ciudad de México; Presencial; MXN 800.000 - 1.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% Company-funded Health and dental plan

Life insurance

Phone finance and home office equipment

30 days Christmas bonus

20 days paid Vacation

50% Vacation premium

13% Saving funds

$2,000 MXN monthly grocery coupons

$2,000 USD annual Co-working Travel perk

$2,000 USD annual Professional Development perk

Catered lunches

Descripción de la vacante

Payjoy is seeking a Machine Learning Engineer in Mexico City responsible for developing, optimizing, and deploying ML models for fraud detection and credit risk. You will collaborate across teams to enhance access to credit in emerging markets, ensuring models are production-ready and continuously improved.

The role requires strong Python proficiency and experience with production-level code. The ideal candidate will contribute to impactful projects aimed at improving financial stability for underserved customers.

Formación

• 3+ years of experience in data science or machine learning roles.
• Proven track record of developing and maintaining ML models.
• Good verbal and written communication skills in English.

Responsabilidades

• Collaborate to deliver data science products in Latam, South Africa, and APAC.
• Design and deploy machine learning models for fraud detection and credit risk.
• Handle large, complex datasets for model accuracy.

Conocimientos

Python

Scikit-Learn

Pandas

Cloud Services (AWS)

Machine Learning

Educación

Bachelor’s degree in Computer Science, Engineering, or a related field

Herramientas

Docker

Databricks

Descripción del empleo

Payjoy is seeking a Machine Learning Engineer in Mexico City responsible for developing, optimizing, and deploying ML models for fraud detection and credit risk. You will collaborate across teams to enhance access to credit in emerging markets, ensuring models are production-ready and continuously improved.

The role requires strong Python proficiency and experience with production-level code. The ideal candidate will contribute to impactful projects aimed at improving financial stability for underserved customers.