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Open nowPosted 99 days ago

IA COMMUNITY

easyapplyrimutee215 open roles

Where
Remote job, Remote
Work mode
Remote
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Your applicationOpen nowIA COMMUNITYeasyapplyrimutee · Remote job, Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on easyapplyrimutee's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.4%3 days
  3. 7.8%7 days
  4. 14.3%14 days
  5. 33.7%30 days
This job: posted 99 days ago

The posting

¡Únete a la Comunidad de Inteligencia Artificial y Arquitectura Avanzada de Rekluti! 🚀🌐

En Rekluti, impulsamos la evolución analítica de las organizaciones. Buscamos científicos de datos y especialistas en Machine Learning que dominen el ciclo end-to-end de los modelos predictivos y su despliegue productivo sobre arquitecturas empresariales en la nube.

Formar parte de este pool te permitirá liderar frentes críticos de ingeniería de características, modelado, interpretabilidad y MLOps, conectando las necesidades del negocio con soluciones de alto impacto y escala masiva.

Tus principales frentes de acción (Visión End-to-End)

  • Ingeniería y Preparación de Datos
  • Modelado y Optimización
  • Despliegue y MLOps
  • Interpretabilidad y Transferencia

Hard Skills & Estándares del Pool

Buscamos profesionales que se ubiquen dentro de los siguientes niveles de especialización técnica:

⚡ Seniority & Experiencia Requerida:

  • Perfiles Senior: Mínimo 5 años de trayectoria liderando proyectos end-to-end de ciencia de datos, con despliegues productivos reales).
  • Perfiles Semi-Senior: Entre 2 y 4 años de experiencia participando activamente en frentes de preparación de datos, modelado técnico y validación funcional.

💻 Stack Tecnológico Requerido:

  • Lenguajes y Librerías: Python experto (pandas, scikit-learn) y dominio avanzado de SQL para modelos tabulares.
  • Ecosistema de Datos Cloud
  • Ecosistema ML & Gobierno

🎓 Si cuentas con certificaciones relacionadas son altamente valoradas

✨ Power Skills & ADN de la Comunidad

  • Mentalidad Resolutiva y Pragmática: Capacidad para traducir un problema complejo de negocio en una arquitectura analítica funcional en producción.
  • Responsabilidad y Confiabilidad: Rigor técnico absoluto en asegurar que los modelos cumplan con los estándares de estabilidad operativos antes del congelamiento (freeze) del dataset.
  • Humildad y Colaboración: Apertura para compartir conocimiento, guiar a otros ingenieros y recibir feedback técnico de manera positiva para potenciar el crecimiento del squad.
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What happens when you press

One press. We do the rest.

  1. A CV for this posting

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  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on easyapplyrimutee's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    easyapplyrimutee's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

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We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

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