Senior Data Scientist at Apex Operations

Aarhus, Central Denmark Region, Denmark -

Full Time

Start Date

Immediate

Expiry Date

16 Sep, 26

Salary

0.0

Posted On

18 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, MLOps, AWS, CI/CD, Model Deployment, Model Monitoring, Backtesting, Statistical Judgement, Linear Programming, Heuristics, Software Engineering, Data Layer Design, Version Control, Drift Detection, Optimization, Operations Research

Industry

International Trade and Development

Description

Are you a senior data scientist who brings both mathematical rigour and production-engineering depth, ready to take our optimization and decision models from working to robust, scalable, and production-ready? Then make a smarter move and unleash your potential as a Senior Data Scientist at Frey. Role & Responsibilities: As a Senior Data Scientist at Frey, you will own our production models end-to-end - from framing and design through to deployment, monitoring, and lifecycle management on AWS. Reporting to the Data Engineering Manager, you will bring operational precision to a team with strong optimization skills, help design a common data layer for our models, and work closely with software engineers and data engineers to ensure our models run reliably in production. Main responsibilities: Own models end-to-end - from framing and design through to a tested, monitored model running in production on AWS. Handle the full operational lifecycle of our models: deployment, monitoring, versioning, drift detection, and lifecycle management. Build evaluation and validation into every model: backtesting, sensible metrics, uncertainty estimates, and a clear view of where a model holds up and where it does not. Help design a common data layer for the models, and evaluate a graph or abstraction layer that decouples models from underlying data sources. Own CI/CD for the model codebase: testing, code review, and releases. Work closely with software and data engineers, and share engineering and operational best practices across the team as it grows. Expected skills & Experience: Significant experience applying data science to production problems — models put into production and kept running. Senior-level depth of ownership matters more than a fixed number of years. Strong Python and software-engineering practice: version control, code review, CI/CD, and testing. Solid MLOps experience: deployment, monitoring, versioning, and drift detection. Strong model evaluation and validation skills, including backtesting, uncertainty estimation, and sound statistical judgement. Experience working on AWS and with CI/CD pipelines. An optimization or operations research background (linear programming, heuristics) is a strong plus. Experience designing data or abstraction layers, feature stores, or graph data models is a plus. Domain knowledge in commodities, freight, shipping, logistics, energy, or finance is a plus, but not required. What matters most is a strong sense of ownership, intellectual curiosity, and the ability to be critical about model limitations. You are proactive about learning new tools, comfortable making design decisions with little supervision, and motivated by working in a high-autonomy environment where your models have direct commercial impact.

Responsibilities

Own the end-to-end production lifecycle of data models on AWS, from design and deployment to monitoring and lifecycle management. Collaborate with software and data engineers to build a common data layer and implement CI/CD best practices for the model codebase.