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Title
Text copied to clipboard!Data Weight Engineer
Description
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We are looking for a skilled Data Weight Engineer to develop and implement advanced algorithms for machine learning and data analysis. The role involves working with large datasets, optimizing models for prediction and decision support, and collaborating closely with interdisciplinary teams to integrate solutions into production environments. The candidate must have a solid understanding of statistics, programming, and system design, as well as the ability to communicate complex technical concepts to non-technical stakeholders. The work requires continuous learning and adaptation to new technologies in artificial intelligence and data science. We offer a challenging position in an innovative environment with opportunities for professional development and career growth.
Responsibilities
Text copied to clipboard!- Develop and implement machine learning models
- Analyze large datasets for insights and patterns
- Optimize algorithms for performance and accuracy
- Collaborate with development teams for solution integration
- Monitor and maintain production systems
- Document methods and results
- Participate in research and development of new technologies
- Present findings to management and stakeholders
- Ensure data quality and integrity
- Contribute to training and mentoring colleagues
Requirements
Text copied to clipboard!- Bachelor's or master's degree in computer science, statistics, or related field
- Experience with programming languages such as Python, R, or Java
- Knowledge of machine learning techniques and tools
- Strong analytical and problem-solving skills
- Experience with databases and data management
- Good communication skills in English and Norwegian
- Ability to work independently and in teams
- Familiarity with cloud platforms like AWS or Azure is a plus
- Experience with big data technologies like Hadoop or Spark
- Interest in continuous professional development
Potential interview questions
Text copied to clipboard!- How do you handle large and complex datasets?
- Can you describe a machine learning model you have developed?
- How do you ensure the quality of the data you use?
- How do you communicate technical concepts to non-technical people?
- Which programming languages are you most comfortable with?
- How do you stay updated on new technology in data science?
- Can you give an example of a challenge you solved in a project?
- How do you collaborate with other disciplines in a project?
