Production-Ready Optimization Data Scientist with MLOps

Avaron AB; Stockholms kommun; On-site; SEK 800,000 - 1,100,000; Full time

Benefits offered by this job

Occupational pension

Wellness allowance SEK 5,000 per year

Job summary

Avaron AB is seeking a role where advanced optimization meets production-ready ML. You will bridge technology and business, turning insights into scalable, robust AI products. You will optimize an existing model, enhance data pipelines, and ensure the deployed solution remains reliable in production on GCP.

Collaboration with Data Scientists, ML Engineers, and Product Managers is key. This is a hands-on role requiring strong Python, optimization expertise, MLOps, and the ability to communicate

Qualifications

• Experience with discrete optimization, IP and MILP.
• Proficient Python, writing clean, production-ready code.
• Experience deploying ML models in the cloud (GCP).
• Hands-on MLOps and CI/CD experience.
• Strong SQL and data wrangling skills.
• Familiar with DBT for data transformation.
• Able to work in Agile, cross-functional teams.

Responsibilities

• Maintain and improve an optimization model and implement enhancements.
• Present outputs to stakeholders and translate business needs into tech solutions.
• Monitor deployed AI product on GCP for performance and reliability.
• Improve data pipelines and integrate new data sources.
• Collaborate with Data Scientists, ML Engineers, and Product Managers.
• Apply MLOps best practices for deployment and lifecycle management.
• Carry out ad-hoc analyses and create visualizations to support decisions.
• Contribute to a Python codebase with clean, production-ready structure.

Skills

Discrete optimization

Python

GCP

MLOps

SQL

DBT

CI/CD

Communication

Job description

Avaron AB is seeking a role where advanced optimization meets production-ready ML. You will bridge technology and business, turning insights into scalable, robust AI products. You will optimize an existing model, enhance data pipelines, and ensure the deployed solution remains reliable in production on GCP.

Collaboration with Data Scientists, ML Engineers, and Product Managers is key. This is a hands-on role requiring strong Python, optimization expertise, MLOps, and the ability to communicate