Data Scientist

Aqilea; Stockholms kommun; Hybrid; SEK 900,000 - 1,300,000; Full time

Job summary

Aqilea in Stockholm is seeking a Data Scientist for a 6–8 month assignment starting 2026-11-15. The role focuses on applied ML, cloud deployment, and building robust data pipelines.

You will lead AI projects, collaborate with stakeholders, and implement MLOps and retrieval pipelines for LLM-based applications.

Qualifications

• 5+ years in data science or applied ML.
• Strong statistics and ML theory knowledge.
• Experience deploying ML models in the cloud beyond notebooks.

Responsibilities

• Develop and deploy ML models in the cloud (beyond notebook coding).
• Lead AI projects and manage stakeholders.
• Build robust data wrangling and data pipelines.
• Establish MLOps and CI/CD pipelines for ML workflows.
• Develop retrieval pipelines and prompt engineering for LLM-based apps.

Skills

Data science

Applied machine learning

Statistics

Python

SQL

MLOps

Cloud deployment (GCP)

Tools

GCP

DBT

LangChain

PyTorch

TensorFlow

Vector databases

CI/CD pipelines

Data wrangling

Job description

About the Assignment

Role: Data Scientist

Job Ref Id: JD-1314

Competence level: 5+

Start date: 2026-11-15

End date: 2027-06-30

Extension option: Yes

Scope: 100%

Location: Stockholm

Remote work: 2 days per week

Language: English

Application deadline: 2026-11-08

Number of consultants: 1

Security clearance: No

We are looking for a candidate with experience in data science and applied machine learning.

Requirements

• 5+ years of experience working in data science or applied machine learning.


• Strong theoretical and practical knowledge in statistics and machine learning.


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


• 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.


• Practical experience with vector databases and embedding models.


• Familiarity with DBT or other data transformation tools.


• Hands-on experience building and deploying ML and LLM based applications, retrieval pipelines, and prompt engineering.


• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, LangChain, or similar.


• Proven experience leading AI projects and stakeholder management.


• Excellent communication skills with the ability to translate complex AI concepts into business-relevant insights.