6 publicaciones de empleo destacadas de data scientist , amazon music en loreto cdmx (¡Están contratando!)

Senior Software Development Engineer
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. - D44 —Ciudad de México, CDMX
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- Administración de personal
- Informática
- Java
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Dotmatics —Ciudad de México, CDMX
- Microsoft Excel
- Administración de personal
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AI Presales
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- Trabajo híbrido
- Español
- Azure
- Doctorado
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DoorDash Mexico —Ciudad de México, CDMX
- Microsoft Excel
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Levi Strauss & Co. —Centro (Área 1), CDMX
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Assistant Scientist
Colgate-Palmolive —Ciudad de México, CDMX
- Administración de personal
- Inglés
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Senior Software Development Engineer

Servicios Comerciales Amazon Mexico S. de R.L. de C.V. - D44 -
Ciudad de México, CDMX

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Información del empleo

Tiempo completo

Cualificaciones

Kotlin
Administración de personal
Informática
C#
Java
SQL
C++
Apache Flink
Licenciatura
JavaScript
Perl
Desarrollo de software
S3
Kafka
Redshift
DynamoDB
Python

Descripción completa del empleo

DESCRIPTION

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.

ABOUT THIS ROLE
As a Senior Software Development Engineer on the Fraud Defense Engineering team, you will be at the forefront of protecting Audible's ecosystem — safeguarding creators, listeners, and customers from fraud and abuse across all global marketplaces. You'll design and build intelligent detection systems, investigation platforms, and automated enforcement capabilities that operate at scale. This is a high-impact role where your technical decisions directly protect the integrity of our business and the trust of millions of customers worldwide.
You'll drive the team forward — anticipating threats before they materialize, innovating on detection approaches, and leading the way to develop original, effective solutions. We'll support you with the latest technologies, tools, and systems you need to succeed.

ABOUT THE TEAM
The Fraud Defense Engineering team sits within Audible's inSpire organization. We build the tooling, platforms, and automated systems that protect the integrity and trustworthiness of Audible's business. Our primary focus areas include:

Creator Fraud — detecting and preventing fraudulent content and manipulation of royalty systems
Anti-Piracy — engineering protections against unauthorized distribution and content theft
Consumer Fraud — identifying and mitigating account abuse, payment fraud, and promotional exploitation

We are also experts in ensuring that Audible meets its data handling and customer privacy obligations across all marketplaces. Joining our team provides the unique challenge and opportunity to deliver software that benefits customers around the world.

ABOUT YOU
You're in your element when you're being challenged, and you're always eager to share your ideas, take on responsibility, and keep developing at an exciting pace. You show initiative, set your standards high, and see every failure as an opportunity to learn. You're looking for an environment where you can thrive, influence technical direction, and help your team reach their potential.

As a Senior Software Development Engineer, you will...

Independently lead complex technical initiatives within the fraud defense domain
Design and build scalable fraud detection systems, such as rule engines, ML-based anomaly detection, and risk scoring pipelines
Architect real-time and batch data processing systems to aggregate fraud signals across multiple marketplaces
Adapt and Build investigation and case management tools that empower internal operations teams
Partner with data scientists, product managers, and policy teams to define enforcement strategies
Mentor and support other developers by cultivating curiosity and deep technical understanding
Write technical design documents and drive alignment across teams
Establish and follow good engineering practices, balancing speed of enforcement with customer experience
Collaborate effectively across time zones with distributed teams

ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

A day in the life

BASIC QUALIFICATIONS

3+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience, or Bachelor's degree in computer science or equivalent
Bachelor's degree or above in computer science, computer engineering, or related field, or experience from a technical internship
1+ years of experience with AWS technologies at scale in a production environment (e.g., Lambda, DynamoDB, SQS, Kinesis, S3, Step Functions)
Experience building and operating near-real-time data processing systems
Proficiency in one or more programming languages such as Java, Python, or Kotlin
Experience with SQL and query engines like Athena or Redshift
Experience with agentic development and design patterns

PREFERRED QUALIFICATIONS

Experience in Trust & Safety, Abuse Prevention, Anti-Fraud, or Risk Engineering domains, with a track record of delivering customer-driven software products at high scale in a fast-paced, technology-first environment
Experience building fraud detection systems — including rule engines, ML-based anomaly detection, behavioral modeling, and risk scoring — with knowledge of AWS SageMaker for ML model deployment
Experience with graph-based analysis for identifying fraud rings, coordinated abuse, or account linking, and familiarity with digital rights management (DRM) or anti-piracy technologies
Proficiency in building data pipelines at scale (ETL/ELT) for aggregating signals across multiple data sources, with hands-on knowledge of PySpark, EMR, and Glue for large-scale data processing
Familiarity with streaming architectures (Kafka, Kinesis, Flink) for near real-time event processing and alerting
Experience with privacy-preserving engineering practices, including data anonymization, GDPR/CCPA compliance, and PII handling
Demonstrated ability to take a lead role in delivering complex software systems, influencing technical direction without direct authority, and navigating complex and ambiguous problem spaces
Experience collaborating across time zones and with geographically distributed teams, working effectively in cross-functional environments

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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