Remote Data & AI Solutions Engineer — End-to-End Impact

Everllence; Roskilde; Hybrid; DKK 600,000 - 900,000; Full time

Benefits offered by this job

Remote work options

Mobility package

Relocation support

Social clubs

Job summary

Everllence seeks a Data / AI Solution Developer to join our Data Management team in PrimeServ Denmark. You will design, build, and improve AI-enabled solutions that blend data, analytics, ML, LLMs, and software development to solve real business challenges.

This role spans the full lifecycle from understanding business needs to deployment and optimization, collaborating with data engineers, developers, analysts, and stakeholders to deliver practical value.

Qualifications

• Hold a degree in Data Science, Computer Science, Software Engineering, Applied Mathematics, Engineering, or a related field.
• Have at least 2 years of experience with data science, analytics, ML, or AI development in a professional setting.
• Solid programming skills, preferably Python, and comfortable with structured data and databases.

Responsibilities

• Design and develop data-driven and AI-enabled solutions that support business processes and decision-making.
• Translate business challenges into technical concepts with stakeholders and domain experts.
• Explore, prepare, and analyze data from multiple sources to identify patterns and directions.
• Develop ML, predictive, or AI-based components for integration into applications/workflows.
• Contribute to the full lifecycle including prototyping, testing, deployment, and monitoring.

Skills

Python

Data science

AI development

Analytics

Education

Bachelor's degree in Data Science, Computer Science, Software Engineering, Applied Mathematics, Engineering

Tools

Azure

SQL

Job description

Everllence seeks a Data / AI Solution Developer to join our Data Management team in PrimeServ Denmark. You will design, build, and improve AI-enabled solutions that blend data, analytics, ML, LLMs, and software development to solve real business challenges.

This role spans the full lifecycle from understanding business needs to deployment and optimization, collaborating with data engineers, developers, analysts, and stakeholders to deliver practical value.