Mid Level Data Scientist Greece
Satalia is hiring a Mid Level Data Scientist Greece for a remote role open to applicants in Greece. Level rates it ; you can apply on Level.
AI in this role
Data Scientist, Greece
Role type: Full time | Location: Greece (fully remote) | Preferred start date: ASAP
ABOUT SATALIA
Satalia builds enterprise-grade AI systems for WPP and its FTSE 100 client base. Led by WPP Chief AI Officer Daniel Hulme, we run as a decentralised organisation where engineers and scientists own their domains end to end. Our data scientists are also at the core of WPP Research, conducting frontier research and developing prototypes that evolve into tools used in production across WPP.
THE ROLE
Our current work includes:
Agentic systems. Developing long-horizon agents that plan, use tools, and collaborate. We also build the core infrastructure to ensure reliability and governance at scale, spanning context/memory, observability, traffic control, and continuous verification.
Federated and privacy-preserving learning. Training shared models when the data cannot move: federated LLM fine-tuning across independent data owners, and aggregation strategies that hold up under heterogeneous datasets.
Identity intelligence. Predictive and probabilistic modelling on large behavioural datasets: propensity and similarity models, and probabilistic record linkage across data sources.
Geospatial intelligence. Spatial statistics, geospatial feature engineering, and forecasting and optimisation over location data, plus computer vision on imagery.
Synthetic data. Generating realistic synthetic data with known ground truth to stress-test models and agents under controlled adversarial conditions.
You will own significant parts of these workstreams: choosing the modelling approach, building the training and evaluation infrastructure, and shipping to production by collaborating with engineers and domain experts across Satalia and WPP.
WHAT YOU'LL DO
· Own well-defined components of a project, from data and modelling to evaluation.
· Develop models, agents, and the evaluation harnesses that keep them safe and reliable.
· Work with engineers to take your work to production.
· Share your work clearly with the team and stakeholders, and support junior colleagues.
· Continously upskill as the field evolves.
MUST HAVE
· 2 to 5 years building ML/AI models in production.
· Strong modelling skills for both structured and unstructured data.
· Hands-on experience building LLM-powered systems.
· Good software engineering habits: Python, version control, testing, code review.
· Clear communication with both technical and non-technical stakeholders.
NICE TO HAVE
· Experience with temporal and geospatial data.
· Experience building and testing agents.
· Experience with federated learning, clean rooms, or other privacy-preserving methods.
· Background in marketing technology, ad tech, audience modelling, or media mix modelling.
· Publications or meaningful open-source contributions.
WHAT WE OFFER
· Healthcare benefits
· Remote working
· Flexible working hours
· Impactful projects
· Continuous learning and development
Satalia is home to some of the brightest minds in AI. If you're looking for a company that values autonomy and freedom and embraces a culture of inclusion and warmth, we'd love to hear from you.
We aim to respond to all applications within 2 weeks. If you have not heard from us within 2 weeks this means your application has been unsuccessful.
By applying to Satalia you are expressly giving your consent for the collection and use of your information as described within our Satalia Recruitment Privacy Policy.
Good luck!
How we rate this
Mid Level Data Scientist Greece at Satalia rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Fine-tuning and Computer vision. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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