PhD Data Sciencist

Workplace: 28906, Getafe

Apply online!

What to expect:

We are looking for a PhD Data Scientist to join a cutting-edge industry-university collaboration project focused on improving industrial manufacturing processes.

Bertrandt's participation will be centered on three key areas:

Enhancing the quality and reducing uncertainty in certifiable surrogate models.
Improving safety in industrial environments.
Developing defect detection and prevention systems in manufacturing.

As part of this project, the selected candidate will be responsible for:

Conducting state-of-the-art research in these areas.
Collecting and analyzing data from various sources.
Developing and implementing Machine Learning models.
Validating models and ensuring their reliability in industrial applications.

What you bring along:

PhD / Doctorate in Data Science or similar.
At least 3 years of experience in Data Science.
Strong programming experience in Python.
Proficiency in Machine Learning libraries (Scikit-learn, CuML), Deep Learning frameworks (TensorFlow, PyTorch), and Explainable AI tools (SHAP, Lime).
Knowledge of Git for version control.
Experience with DVC for data management.
Familiarity with MLOps frameworks for model deployment (MLflow, Airflow).
Strong soft skills for collaboration and research.
Minimum B2 level of English.

We are Bertrandt.

An independent and international development service provider with long years of automotive expertise. With cross-industry know-how and a holistic understanding of systems and products, we create technological solutions at any stage of the product development process. We deal with a focus on hot topics such as digitalization, e-mobility and autonomous systems, mainly for the automotive, aerospace and mechanical engineering sectors, and consistently facilitate the development of tailored solutions in these areas. Our goal: to accelerate technological progress and make a relevant contribution to a sustainable future. We work on this every day – with around 14,000 employees at more than 50 sites worldwide.