Data Scientist (Early Hire) — Full ML Ownership, B2C SaaS

Jobgether

Málaga

Presencial

EUR 60.000 - 90.000

Jornada completa

Hace 5 días
Sé de los primeros/as/es en solicitar esta vacante
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Ventajas ofrecidas por este puesto de trabajo

22 days paid time off

Descripción de la vacante

Jobgether is seeking a Data Scientist Early Hire to own full model lifecycle for a B2C SaaS product in a remote-friendly setup across Europe. You will lead model design, development, deployment, monitoring, and optimization with direct impact on product strategy and revenue growth.

You will work closely with Product, Growth, Engineering, and Finance to translate data into actionable insights, shape experimentation programs, and build scalable ML practices from the ground up, with high autonomy

Formación

  • 3+ years building and deploying ML models in production.
  • Strong Python/SQL and ML framework experience.
  • Ability to own projects end-to-end with stakeholders.
  • Familiarity with experimentation and causal inference is a plus.

Responsabilidades

  • Design, build, validate, deploy, and monitor ML models aligned to business goals.
  • Own complete ML lifecycle from feature engineering to deployment and monitoring.
  • Monitor production models and adapt to changing user behavior.
  • Design experiments including A/B tests and causal inference.
  • Build scalable data pipelines and feature stores with data engineers.
  • Translate model findings into actionable business recommendations.

Conocimientos

Python
SQL
Machine learning
Experimentation

Herramientas

scikit-learn
PyTorch
TensorFlow

Descripción del empleo

Jobgether is seeking a Data Scientist Early Hire to own full model lifecycle for a B2C SaaS product in a remote-friendly setup across Europe. You will lead model design, development, deployment, monitoring, and optimization with direct impact on product strategy and revenue growth.

You will work closely with Product, Growth, Engineering, and Finance to translate data into actionable insights, shape experimentation programs, and build scalable ML practices from the ground up, with high autonomy

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