Data Scientist

Job summary

As a Data Scientist, you will work on integrating data and machine learning to enhance fraud prevention, risk management, and business growth. You will be part of a team based in Aarhus, collaborating closely with engineers, analysts, and stakeholders.

Qualifications

• Proven experience in developing and deploying machine learning models in production settings.
• Proficient in Python and familiar with ML libraries such as scikit-learn, TensorFlow, and PyTorch.
• Experience with cloud-based ML platforms like AWS SageMaker or Kubeflow.
• Strong foundation in machine learning, statistical modeling, and data analysis techniques; experience in financial services is advantageous.
• Excellent problem-solving and communication skills, capable of translating technical concepts into business insights.

Responsibilities

Benefits and perks

• Design, build, and deploy machine learning and statistical models for fraud detection, transaction monitoring, loan risk assessment, and customer risk scoring.
• Create and manage experimentation and evaluation frameworks using tools like MLflow and Metaflow, ensuring robust test sets and benchmarks.
• Conduct data analysis and feature engineering to enhance model performance.
• Collaborate with data engineers, analysts, and business stakeholders to define requirements and convert insights into actionable decisions.
• Document models, methodologies, and results clearly, incorporating the latest advancements in machine learning and generative AI.
• 4 days in the office, fostering a collaborative team environment.
• Access to state-of-the-art equipment to support optimal performance.
• Comprehensive benefits including pension, health insurance, and enhanced parental leave.