11 publicaciones de empleo destacadas de data scientist en parque del pedregal, dif (¡Están contratando!)

Machine Learning Engineer - Fraud
PayJoy —Ciudad de México, CDMX
- Tiempo completo
- Informática
- Inglés
- Experiencia en bases de datos
- Seguro dental
- Seguro de la vista
Sr. Financial Analyst, MX Marketing and Prime Finance
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Microsoft Access
- Oracle
- Inglés
Product Manager - AI/ML - Cybersecurity, Identity, Network Security
Delinea —Ciudad de México, CDMX
- Tiempo completo
- Administración de personal
- Gestión de productos
- Seguro de vida
ELN Analyst (Benchling)
Zifo —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Maestría
- Licenciatura
Postulación rápida
Clinical Scientist in CNS - LATAM
IQVIA —Ciudad de México, CDMX
- Tiempo completo
- Inglés
- Maestría
Staff Software Engineer - Data Processing & Execution Platform
Dotmatics —Ciudad de México, CDMX
- Microsoft Excel
- Administración de personal
- Informática
Associate Account Manager
Konovo —Ciudad de México, CDMX
- Home Office (Desde casa)
- Microsoft Excel
- Administración de personal
- Salesforce
Fullstack AI Software Engineer - LATAM
Futureproofing —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- JavaScript
- Python
Digital Media Strategist - MX
WITHIN —Ciudad de México, CDMX
- Contacto por teléfono
- Microsoft Excel
- Inglés
- Licenciatura
AI Presales
SDG Group —Ciudad de México, CDMX
- Trabajo híbrido
- Español
- Azure
- Doctorado
Postulación rápida
Senior Data Scientist, DTC
Levi Strauss & Co. —Centro (Área 1), CDMX
- Tiempo completo
- Doctorado
- Informática
- Maestría
Postulación rápida
10d

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Analista de información
Seg —Coyoacán, CDMX
Experiencia en análisis de datos. Licenciatura concluida (Estadística, Ingeniería Industrial, Sistemas, Informática, Ciencia de datos, Actuaría o carreras afin)…
$15,000 por mes
Postulación rápida
2d
Analista de Datos jr
Muebles para Baño —Venustiano Carranza, CDMX
Experiencia ó conocimiento en modelado de datos y bases de datos relacionales. ETL y transformación de datos. Diseñar modelos de datos eficientes para análisis…
$14,000 a $15,000 por mes
Postulación rápida

Quiero recibir la alerta de empleo más reciente para data scientist en parque del pedregal, dif

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Machine Learning Engineer - Fraud

PayJoy -
Ciudad de México, CDMX

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Información del empleo

Tiempo completo

Beneficios

Seguro dental
Seguro de la vista
Seguro de vida

Cualificaciones

Informática
Inglés
Experiencia en bases de datos
Pandas
Docker
Licenciatura
Flask
Bases de datos orientadas a grafos
Python

Descripción completa del empleo

About PayJoy

PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system. Through PayJoy’s point-of-sale financing and card offerings, customers gain access to a modern quality of life. PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 million customers as of 2025 while achieving solid profitability for sustainable growth.

This role

As a Machine Learning Engineer, you will be responsible for developing, optimizing and deploying the ML models and infrastructure that power our fraud detection capabilities across all of PayJoy’s products and markets.

You will work closely with fraud, engineering, product, risk, and business stakeholders across diverse markets to drive the design, implementation and scaling of ML models, AI agents, and other data products (fraud review queues, transaction authorization system, etc.). Your role will also involve ensuring that we are continuously improving the quality and performance of our models by gathering and integrating new data sources that enhance our predictive capabilities.

You will own the whole lifecycle of our fraud ML models, from the feature generation to the model rollout (design, development, deployment and monitoring). You will also build infrastructure to support both manual and automated decisioning of fraud risk.

You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to our millions of users across the countries we operate in.

Responsibilities

Collaborate with global teams including Fraud, Engineering, Product, and Risk to deliver world-class data science products to international markets in Latam, South Africa and APAC.
Design, build, and deploy machine learning models for fraud detection use cases across PayJoy’s product suite
Ensure our delivered ML models are production-ready, optimized for scale and continuously improved based on feedback from our stakeholders and performance in production.
Improve our infrastructure for fraud decisioning by extending it to new entity types, identifying and constructing new rules, and supporting greater scale as we grow.
Handle large, complex datasets to clean, preprocess and extract relevant features to improve product accuracy and performance.

Write production-level code with documentation, testing and peer review.
Work with a data-driven mindset and understand the critical importance of handling data properly and safely.
Lead the testing, cost-benefit analysis and integration of new data sources to improve the accuracy and robustness of our ML models.

Work closely with our ML Platform and Tooling team to design and implement scalable feature generation and extraction pipelines and model deployment/monitoring processes.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field
3+ years of experience as a data scientist, machine learning engineer, data engineer or a closely related position with a proven track record of writing production-level code and developing and maintaining ML models in production.
High proficiency in Python and a strong understanding of its related libraries and frameworks (e.g., Scikit-Learn, Pandas, Flask, etc).
Comprehensive knowledge of ML lifecycle: from data extraction and feature engineering to model serving and monitoring for live and batch processing.
Demonstrated experience with cloud providers (AWS preferred) and related services like containerization (e.g., Docker).
Experience in fraud detection or other applications of machine learning in the financial market is a big plus.
Experience with LLMs or graph databases is also a plus.
Hands-on experience with Databricks for developing, deploying and monitoring machine learning workflows at scale is another plus.
Good verbal and written communication skills in English
Ability to work in a fast paced environment with constant requirement changes.

Benefits

100% Company-funded Health and dental and vision discount plan for employees and immediate family members.
Life insurance.
Phone finance, Headphone, home office equipment and wellness perks.
30 days of 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

PayJoy is proud to be an Equal Employment Opportunity employer and we welcome and encourage people of all backgrounds. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

PayJoy Principles

Finance for the next billion * Ownership * Break Through Walls * Live Communication * Transparency & Directness * Focus on Scale * Work-Life Balance * Embrace Diversity * Speed * Active Listening

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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data scientist empleos en parque del pedregal, dif

Machine Learning Engineer - Fraud

Sr. Financial Analyst, MX Marketing and Prime Finance

Product Manager - AI/ML - Cybersecurity, Identity, Network Security

ELN Analyst (Benchling)

Clinical Scientist in CNS - LATAM

Staff Software Engineer - Data Processing & Execution Platform

Associate Account Manager

Fullstack AI Software Engineer - LATAM

Digital Media Strategist - MX

AI Presales

Senior Data Scientist, DTC

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