Data Scientist

Electronic Toll Collection (Pty) Ltd; Madrid; Híbrido; EUR 50.000 - 70.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Permanent role

Hybrid working model

Flexible working hours

30 business days annual leave

Flexible remuneration plan

Descripción de la vacante

Kapsch is seeking a Data Scientist with experience developing machine learning solutions and analytics models, from experiments to production-ready systems.

You will work closely with Product Owners, Data Engineers, MLOps Engineers, and Data Analysts to transform business challenges into scalable AI solutions and data products. The role includes forecasting and time-series modeling with strong emphasis on end-to-end delivery.

Formación

• 4+ years of experience in data science or ML engineering.
• Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field.
• Strong background in machine learning.
• Experience managing ML experimentation cycles, model lifecycle, and production maintenance with tools like MLflow.
• Proficiency in Python and SQL.

Responsabilidades

• Design, develop, and validate ML models through iterative experimentation and PoC cycles.
• Work with customers and stakeholders to define use cases, KPIs, and success criteria.
• Develop forecasting, predictive, and analytical models, with a focus on time series.
• Collaborate with Product Owners, Data Engineers, Data Analysts, and MLOps to deliver AI solutions.
• Perform feature engineering, model validation, and performance analysis.
• Build demo-ready PoCs and visualizations to communicate results to stakeholders.
• Track experiments and model evolution using MLflow.
• Work with analytical datasets and define features for ML use cases.
• Contribute to AI/ML solution design and best practices.

Conocimientos

Data Science

Python

SQL

Machine Learning

Time Series

Educación

Bachelor's degree in Data Science/CS/Math

Herramientas

MLflow

Apache Airflow

Pandas

NumPy

SQL

Descripción del empleo

Kapsch is one of Austria's most successful global technology companies. With its comprehensive ITS (Intelligent Transportation Systems) portfolio, Kapsch is actively addressing the challenges of the present and the future with intelligent mobility solutions in a wide range of application areas. As a family-owned company founded in 1892 and headquartered in Vienna, Kapsch can look back on 130 years of experience with the future. To learn more about our solutions and innovations, visit our website here.

Role Purpose

We are looking for a Data Scientist with experience developing machine learning solutions and analytical models, from experimentation to validated production-ready models. You will work closely with the Product Owner, Data Engineers, MLOps Engineers, and Data Analysts to transform business challenges into scalable AI solutions and data products.

How You'll Make An Impact

• Design, develop, and validate machine learning models through iterative experimentation and PoC cycles.
• Work directly with customers and stakeholders to understand business problems, define use cases, KPIs, and success criteria.
• Develop forecasting, predictive, and analytical models, with strong focus on time series use cases.
• Collaborate closely with Product Owners, Data Engineers, Data Analysts, and MLOps Engineers to deliver AI and ML solutions efficiently.
• Perform feature engineering, model validation, and model performance analysis.
• Build demo-ready PoCs and visualizations to communicate results and insights to stakeholders.
• Track experiments, metrics, and model evolution using MLflow.
• Work with analytical datasets and contribute to the definition of datasets and features for ML use cases.
• Contribute to technical standards, best practices, and AI/ML solution design.

What Makes You a Great Fit

• 4+ years of experience as a Data Scientist, ML Engineer, or similar role focused on analytical and ML solutions.
• Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field.
• Strong background in machine learning.
• Experience managing ML experimentation cycles, model lifecycle, and production model maintenance, using tools such as MLflow or similar.
• Proficiency in Python and experience working with SQL.
• Experience working with analytical databases and large datasets.
• Familiarity with orchestration tools such as Apache Airflow and notebook-based experimentation workflows.
• Strong English communication skills, both written and spoken.
• Analytical mindset, fast learner, collaborative attitude, and customer-oriented approach.
• Experience working in Agile environments.

Our Offer to You

• Permanent role.
• Hybrid working model (3 days of remote work/week).
• Flexible working hours.
• 30 business days of annual leave.
• Flexible remuneration plan.