4 publicaciones de empleo destacadas de data scientist en cdmx (¡Están contratando!)

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 Datos / Business Intelligence Analyst (BI) - Home Office
Master Loyalty Group —Ciudad de México, CDMX
Lunes a Viernes 09 00 AM a 06 00 PM. Excel avanzado: tablas dinámicas, fórmulas, validaciones y limpieza de datos. Sueldo: $16,000.00 al mes.
$16,000 por mes
Postulación rápida
3d
Digital Marketing - Data Science AppsFlyer
Accenture —Ciudad de México, CDMX
¡ATRÉVETE A SER PARTE DEL DESAFÍO! ¡VEN Y ÚNETE A NUESTRO EQUIPO JUNTOS PODEMOS MARCAR LA DIFERENCIA! ¿Sabías que Accenture está liderando la transformación…

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Fullstack AI Software Engineer - LATAM

Futureproofing
Ciudad de México, CDMX

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Información del empleo

Tiempo completo

Cualificaciones

Ingeniería de software
JavaScript
TypeScript
Python

Descripción completa del empleo

Location: Remote - Based in Argentina, Brazil, or Peru.

Contract Type: Independent contract, part-time and full-time available

Compensation: Based on leveling. Senior-level engineers (L5+) - $6,000-8,00 USD monthly retainer for full-time. Staff+ level engineers - $10,000-12,000 USD monthly retainer for full-time

About Futureproofing

Futureproofing builds AI-native founding teams for companies creating new products, launching new ventures, or transforming existing businesses around AI.

Our engineers work alongside founders, product leaders, data scientists, and business teams from problem definition through architecture, launch, and iteration.

We’re looking for builders who can take ownership of ambiguous problems and turn them into excellent production products—not engineers waiting for a perfectly defined ticket.

What You’ll Do

Own AI products and features from problem definition through production
Work directly with founders, executives, and subject-matter experts
Design and build systems using LLMs, agents, retrieval, structured data, APIs, and traditional software
Make thoughtful tradeoffs across quality, evaluation, latency, cost, reliability, and complexity
Build evaluation and feedback loops that tell us whether AI systems are actually working
Move quickly from prototype to production without sacrificing engineering quality
Push back when a technical or product direction doesn’t make sense—and explain why
Use AI deeply in your own engineering workflow while applying strong judgment and guardrails

What We’re Looking For

5+ years of professional software engineering experience
Experience owning and shipping real production products
Meaningful experience building AI-powered products in production
Strong Python and/or TypeScript/JavaScript skills with comfort across the stack
Experience with modern AI architectures such as agents, tool use, RAG/retrieval, structured generation, and evaluation
Strong product judgment and comfort operating with significant autonomy
Clear communication with both technical and nontechnical stakeholders
Genuine curiosity about AI—you actively experiment with new tools and continuously evolve how you build

We especially value engineers with 0 1 experience, startup backgrounds, customer exposure, or ownership beyond a narrow technical specialty.

You don’t need to know everything. You do need to be rigorous and deeply curious.

How We Work

Futureproofing is fully remote, with engineering talent primarily across Latin America and clients primarily in the United States.

Engagements may be part-time or full-time, with some US working-hour overlap. You’ll work closely with Futureproofing’s engineering leadership while working on a dedicated client founding team.

What Makes Futureproofing Different

Small, senior teams. We build teams around problems, not seats.

Real ownership. Engineers participate in architecture, product decisions, tradeoffs, and client conversations—not just implementation.

Production AI. We care about systems that survive contact with real users, data, and business constraints.

AI-native engineering. We expect our engineers to experiment constantly with how AI changes the way software is built.

Intentional matching. We get to know our engineers and clients deeply rather than matching through keywords.

Developer-first. We’d rather build a smaller network of exceptional engineers doing meaningful work than optimize for placement volume.

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data scientist empleos en cdmx

Fullstack AI Software Engineer - LATAM

Digital Media Strategist - MX

AI Presales

Senior Data Scientist, DTC

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