Senior Data Scientist

emagine is looking for a Senior Data Scientist with deep expertise in Linear Integer Programming and a robust background in analytics and strong skills in MLOps.

Start: 17th of August

Length: 6 months with possible extension

Location: Stockholm/hybrid (must be on-site minimum 3 days per week)

In this role, you will be instrumental in developing, maintaining, and scaling production-grade optimization models. The ideal candidate has a strong background in Linear Integer Optimization and MLOps, with the ability to handle everything from complex data wrangling to presenting clear results to our stakeholders. This role goes beyond just creating plots and presentations; you must be able to deliver clear messages to stakeholders and actively incorporate their feedback back into the AI product.

Because this role involves working within a sophisticated Python codebase, you should have a solid understanding of software architecture and feel comfortable maintaining AI models in a production environment. We specifically use Google Cloud Platform (GCP) for our data and deployment workflows, so experience with the GCP ecosystem is essential. Above all, we need a proactive team player who can take ownership of their work while collaborating closely with others to ensure our models remain reliable and effective.

Responsibilities

• Maintain and enhance the existing optimization model by proactively identifying shortcomings and implementing improvements.

• Present model outputs and analytical findings to stakeholders, gather and translate business requirements into technical solutions, and maintain clear, consistent communication with all stakeholders throughout the project lifecycle.

• Ensure the robustness and efficiency of the deployed AI product on GCP through continuous monitoring and maintenance.

• Improve the data preparation and wrangling pipeline, and integrate additional data sources to enrich model inputs.

• Collaborate with Data Scientists, ML Engineers, and Product Managers to improve the performance, reliability, and scalability of the optimization model.

• Implement MLOps best practices for seamless deployment, monitoring, and lifecycle management of machine learning models.

• Conduct ad-hoc data analyses and develop visualizations to support data-driven decision-making across teams.

Required Skills

• Solid knowledge and experience in discrete optimization models (Integer Programming, Mixed Integer Programming)

• Proven experience developing and deploying ML models in the cloud, preferably on GCP (beyond notebook-based coding and execution).

• Solid Python programming skills-writing clean, efficient, modular, and production-ready code that is easy to maintain and test.

• Hands-on experience with MLOps and CI/CD pipelines, ideally on GCP.Strong SQL skills for data manipulation and analysis.

• Ability to understand diverse data sources and build robust data wrangling and aggregation pipelines.

• Familiarity with DBT for data transformation.

• Comfortable working in Agile, cross-functional teams.

• Strong collaboration skills and ability to thrive in complex, ambiguous problem domains