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Jobs in Tijuana, United States

Fraud Analytics Director

PayJoy

Mexico
Remote
MXN 1,840,000 - 2,393,000
5 days ago
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DOCENTE MARKETING

Grupo IOE - Formación de calidad para empresas

Estado de México
Remote
MXN 200,000 - 400,000
5 days ago
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Customer Success Advisor

HighLevel

Mexico
Remote
MXN 1,104,000 - 1,473,000
5 days ago
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Senior Full-stack Engineer (.Net/JavaScript) - Finance (Latam)

Truelogic

Mexico
Remote
MXN 920,000 - 1,473,000
5 days ago
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DOCENTE INGLÉS TECNICO SANITARIO

Grupo IOE - Formación de calidad para empresas

Estado de México
Remote
MXN 50,000 - 200,000
5 days ago
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Quote Pricing Specialist (Linguistic Solutions)

IQVIA

Ciudad de México
Remote
MXN 500,000 - 700,000
5 days ago
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Manager, Application Engineering

Zillow

Ciudad de México
Remote
MXN 2,208,000 - 3,313,000
5 days ago
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Senior Product Marketing Specialist

Tala

Ciudad de México
Remote
MXN 600,000 - 900,000
5 days ago
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Observability Engineering Manager

Working Nomads

Ciudad de México
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MXN 1,840,000 - 2,577,000
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Teleoperador Bilingüe

Oberstaff

Estado de México
Remote
MXN 50,000 - 200,000
5 days ago
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Business Operations Principal - Pro

P2P

Ciudad de México
Remote
MXN 200,000 - 400,000
5 days ago
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DOCENTE COM314_3 GESTIÓN COMERCIAL DE VENTAS

Grupo IOE - Formación de calidad para empresas

Estado de México
Remote
MXN 200,000 - 400,000
5 days ago
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Software Engineer II - Practice Engagement (Mexico)

Dandy

Ciudad de México
Remote
MXN 828,000 - 1,197,000
5 days ago
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Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics

Canonical

Mérida
Remote
MXN 1,288,000 - 1,657,000
5 days ago
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Coach Académico

Learning Heroes

Ciudad de México
Remote
MXN 200,000 - 400,000
5 days ago
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Senior AI Engineer

Nexaminds

Región Centro
Remote
MXN 400,000 - 600,000
5 days ago
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Practicante No Remunerado de Gestión de Campañas de Mail

GAOTek Inc

Mérida
Remote
MXN 50,000 - 200,000
5 days ago
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Growth Backer - Highest Paying Position

Cyberbacker Careers

Veracruz
Remote
MXN 400,000 - 600,000
5 days ago
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Convocatoria Profesor/a UDEM Online (Educación, Humanidades)

Universidad de Monterrey

San Pedro Garza García
Remote
MXN 200,000 - 400,000
5 days ago
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Maquila por pieza o destajo

M &Service man S.A de C.V

Ciudad de México
Remote
MXN 200,000 - 400,000
5 days ago
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Salesforce Client Success (Agile Delivery) - Mexico (Remote)

EmergencyMD

Región Centro
Remote
MXN 600,000 - 900,000
6 days ago
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Data Analyst

Ingenia Group Internet Desarrollo, S.A.P.I. de C.V.

Ciudad de México
Remote
MXN 400,000 - 600,000
6 days ago
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Client Support Lead (JOB ID: IOHCSM)

Inside Out

Mexico
Remote
MXN 200,000 - 400,000
6 days ago
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Java Fullstack Developer 2636

Xideral

Región Centro
Remote
MXN 200,000 - 400,000
6 days ago
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Principal Biostatistician, FSP

IQVIA

Ciudad de México
Remote
MXN 1,288,000 - 2,025,000
6 days ago
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Fraud Analytics Director
PayJoy
Mexico
Remote
MXN 1,840,000 - 2,393,000
Full time
5 days ago
Be an early applicant

Job summary

A leading financial technology company is seeking a Director of Global Fraud Analytics to optimize anti-fraud systems and lead a team. The ideal candidate has extensive experience in fraud prevention and strong analytical skills. This role offers unique professional development perks and the opportunity to influence financial security across emerging markets.

Benefits

Co-working Travel perk ($2,000 USD annually)
Professional Development perk ($2,000 USD annually)
Phone finance and home office equipment

Qualifications

  • 7+ years of experience optimizing user anti-fraud systems.
  • Proficiency in Python and its libraries.
  • Strong leadership skills with experience managing teams.

Responsibilities

  • Optimize anti-fraud tools to protect distribution networks.
  • Develop analytics models to detect and prevent fraud.
  • Lead the development of new anti-fraud tools.

Skills

Python
Analytical skills
Leadership
Machine Learning
Data analysis

Education

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

Tools

AWS
Docker
Scikit-Learn
Pandas
Flask
Job description
Overview

About PayJoy

PayJoy is a mission-first financial service provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. We lend through our patented technology that turns a smartphone into digital collateral, and our cutting-edge machine learning, data science, and anti-fraud AI allow us to offer the lowest cost and qualify the most customers in the industry. As of 2025 we have brought billions of dollars in credit to 15 million customers, doubling in the last two years while remaining strongly profitable and sustainable for the long term.

This role

The Director of Global Fraud Analytics is responsible to lead the fraud analytics team responsible for optimizing PayJoy’s automated anti-fraud systems that balance the seamless end user experience with great fraud and to build and integrate new tools focused on using data as a competitive advantage and includes PayJoy’s core quantitative functions such as Risk Strategy, Fraud Strategy, Portfolio Valuation, Machine Learning and Data Science.

Responsibilities
  • Optimize PayJoy’s automated anti-fraud tools that protect our distribution networks, card transactions and user onboarding systems.
  • Develop and implement advanced analytics models to detect and prevent fraud across all markets where PayJoy is present.
  • Independently analyze fraud trends, writing queries and code to optimize strategies to identify patterns and trends in fraudulent activities.
  • Lead the development or procurement of new tools that accomplish anti-fraud objectives and deliver value.
  • Own and improve rules, thresholds, and ML models in collaboration with Data Science.
  • Clearly communicate your vision and partner with multiple teams to execute on your strategy.
  • Mentor and continue building PayJoy’s Fraud Analytics team
  • Stay updated on the latest trends and technologies in data analytics and fraud detection.
Requirements
  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • 7+ years of experience optimizing and designing globally large scale user anti-fraud systems with quantitative methods as an ultra growth Fintech company.
  • Strong leadership and people management skills with at least 2 years of experience leading and scaling high-performing teams.
  • 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 life cycle: 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 credit risk modeling, fraud detection or other applications of machine learning in the financial market is a big plus.
  • Good verbal and written communication skills in English
  • Ability to work in a fast paced environment with constant requirement changes.
Benefits
  • *Local benefits may vary depending on the country of hire*
  • Phone finance, Headphone, home office equipment and fitness perks.
  • $2,000 USD annual Co-working Travel perk
  • $2,000 USD annual Professional Development perk

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

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

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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