Data Scientist (m/f/d)

Nordex Portugal is looking for team members in Porto.

 

YOUR TASKS

As an Data Scientist, you will build predictive maintenance solutions for our wind turbines and join one of the top teams in the industry in this field of work. You’ll find innumerable opportunities in the company to put your AI skills to practice, and be challenged by the variety, volume, and velocity of data to work with.

More precisely, you’ll:

• Build end-to-end machine learning solutions (data pipelines to deployed models) on on-premise infrastructure or the cloud

• Engage with internal and external experts to identify opportunities for the application of predictive maintenance or machine learning in general

• Build and test proofs-of-concept in controlled environments, and scale-up for use in production

• Collaborate with fellow ML experts and data engineers to improve performance of existing ML solutions

• Build solutions to monitor performance and accuracy of models in deployment, and take corrective measures where necessary

 

YOUR PROFILE

Essential

• Education background in computer science or comparable stream

• Strong skills programming in R

• Minimum three years experience developing complex machine learning models included demonstrated use of XGBoost and Keras/Tensorflow

• Experience building performant and accurate models on big data

• Experience deploying ML models to the cloud using CI/CD workflows and Docker

• Experience working in agile projects

• Fluent in English; ability to speak Spanish or German is a plus

• Constant learner to stay on top of technology developments for continuous improvement of solutions

Desirable

• Extensive knowledge of ML frameworks, data structures and modelling, and software architecture to build cloud-friendly solutions

• Basic understanding of Python/Matlab welcome

• Experience working in industries where heavy machinery operate

 

Please provide the CV in english

Nordex adheres to a policy of equal employment opportunity. All employment decisions are made without regard to religion, age, sex, color, national origin, handicap, or other protected class and in full compliance with all federal and state laws.