Senior Data Scientist

Securitas Group

Lead design and production deployment of ML and GenAI solutions at Securitas. Collaborate with AI team to drive actionable intelligence from data for security solutions.

Posted 5/9/2026full-timeMalmö • 🇸🇪 SwedenSeniorWebsite

Tech Stack

Tools & technologies

DockerPython

About the role

Key responsibilities & impact

Owning the architecture of LLM-powered pipelines that extract structure and insight from large volumes of unstructured text, such as incident reports, operational logs, client data.
Designing and stress-testing end-to-end GenAI architectures (e.g. RAG), prompt strategies, and evaluation frameworks - relevance, faithfulness, hallucination rates, latency tradeoffs - and setting the bar for what 'good' looks like on the team.
Building and productionizing workforce management models - demand forecasting, shift scheduling optimization, and attrition modeling - that help deploy officers more effectively.
Developing client churn models that give the business early, actionable retention signals.
Driving the end-to-end ML lifecycle: from problem framing and data strategy through to monitored, production-grade systems.
Translating ambiguous business problems into concrete technical roadmaps - and pushing back when the framing is wrong.
Mentoring junior data scientists and setting technical standards across the team.
Presenting findings, model behavior, and tradeoffs to senior stakeholders clearly and credibly.

Requirements

What you’ll need

Around 5+ years of professional data science experience, with a clear track record of successes.
Deep Python skills and strong software engineering habits - your code is readable, tested, and maintainable.
Advanced NLP experience and hands-on work with LLMs at a level beyond prompt experimentation - fine-tuning, evaluation, deployment.
A rigorous approach to GenAI evaluation : you've built frameworks to measure output quality, catch failure modes, and make principled tradeoffs with full lifecycle thinking.
Experience with MLOps fundamentals : deployment, serving, and monitoring of models, CI/CD, Docker, application and service logging, and reproducible pipelines.
Using modern AI coding tools to work as a highly productive data scientist - rapidly exploring ideas, writing and refactoring code, and debugging faster while keeping a critical eye on outputs.
Strong analytical instincts - you can tell when a result is too good to be true and you know how to find out why.
Communication skills sharp enough to run a stakeholder presentation and a code review on the same day.

Benefits

Comp & perks

At Securitas we believe in doing the right thing and doing it well.
Our employees come from all walks of life and bring with them many talents and perspectives.
We aim for diverse representation throughout the company, and we are committed to equal pay, safe working conditions, gender balance and an inclusive work environment with a wide range of skills and development opportunities.

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Hard Skills & Tools

PythonNLPLLMsGenAIMLOpsdemand forecastingshift scheduling optimizationattrition modelingclient churn modelsmachine learning lifecycle

Soft Skills

mentoringcommunicationanalytical instinctsproblem framingstakeholder presentationtechnical standardspushing backclarity in findingscollaborationcritical thinking