Junior Analytics & ML Engineer (Hybrid) — Build AI Pipelines

Hedvig Försäkring AB; Stockholms kommun; Hybrid; SEK 420,000 - 600,000; Full time

Job summary

Hedvig Försäkring AB seeks a Junior Analytics & ML Engineer to help develop the core data model and ML/AI infrastructure powering pricing, reporting, recommendations, and a customer service bot.

Working with backend developers, data scientists, and business teams, you will shape data architecture and agentic AI development to fuel growth, with opportunities to deploy your own models and contribute to automated decision-making.

Qualifications

• Master’s in Computer Science, Data Engineering, Engineering Physics, Mathematics, or related quantitative field
• 0–2 years of experience with a modern data stack (BigQuery, dbt, Looker) or deploying ML infrastructure
• Proficiency in SQL to architect data prep and feature engineering pipelines
• Proficiency in Python and standard DS libraries for scalable ML architecture
• Experience with cloud platforms (GCP, AWS, or Azure) and MLOps practices
• Interest in modern AI stack (LLMs, RAG, prompt engineering) to accelerate data/ML platforms

Responsibilities

• Architect and scale our core data model and data pipelines
• Design and build ML/AI infrastructure and deployment platform
• Drive data and infrastructure projects from definition to deployed solutions
• Design and deploy ML models contributing to automated decision-making
• Collaborate with backend engineers, data scientists, analysts, and business teams to shape data architecture

Skills

SQL

Python

Data modeling

MLOps

Data warehousing

Education

Master's in Computer Science

Data Engineering or related quantitative field

Tools

BigQuery

Looker

dbt

GCP

AWS

Azure

Job description

Hedvig Försäkring AB seeks a Junior Analytics & ML Engineer to help develop the core data model and ML/AI infrastructure powering pricing, reporting, recommendations, and a customer service bot.

Working with backend developers, data scientists, and business teams, you will shape data architecture and agentic AI development to fuel growth, with opportunities to deploy your own models and contribute to automated decision-making.