Data Scientist Greece

Satalia; United States; Remote; USD 34,000 - 40,000; Full time

Benefits offered by this job

Healthcare benefits

Remote working

Flexible working hours

Impactful projects

Continuous learning and development

Job summary

Satalia, a creator of enterprise AI systems, invites applications for a Junior Data Scientist role in a fully remote Greece setting. You will explore multimodal datasets, craft features, and build models and agents guided by senior data scientists.

You will write clean, tested code ready for production, learn across workstreams, and adapt to evolving AI methods while collaborating with cross-functional teams.

Qualifications

• Degree in computer science, statistics, mathematics or related quantitative field; MSc/PhD is a plus.
• 0–2 years of experience in data science or machine learning, including internships or substantial academic projects.
• Solid foundations in statistics and machine learning for structured and unstructured data.
• Good Python skills and familiarity with the standard data science stack.
• Hands-on experience with embeddings and LLM-based solutions.
• Curiosity, a willingness to learn, and clear communication.
• Experience with temporal or geospatial data; open-source contributions/publications/competition results.

Responsibilities

• Explore multimodal datasets and build the features and pipelines that models depend on.
• Build and test models and agents under the guidance of senior data scientists.
• Write clean, tested, reviewed code that is ready to go to production.
• Learn quickly across workstreams and pick up new methods as the field evolves.

Skills

Python

ML basics

Embeddings

LLM solutions

Geospatial data

Temporal data

Communication

Education

Bachelors in CS/Statistics/Math

MSc or PhD (preferred)

Tools

NumPy/Pandas

PyTorch/TensorFlow

Job description

Junior Data Scientist, Greece Role type: Full time | Location: Greece (fully remote) | Preferred start date: ASAP

Описание:

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. 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 work across these workstreams alongside senior data scientists, engineers, and domain experts across Satalia and WPP, building and testing models and agents that ship to production.

Задачи:

Explore multimodal datasets and buildthe features and pipelines that models depend on. Build and test models and agents under the guidance of senior data scientists. Write clean, tested, reviewed code that is ready to go to production. Learn quickly across workstreams and pick up new methods as the field evolves

Требования:

A degree in computer science, statistics, mathematics, or a related quantitative field. An MSc or PhD is a plus. 0 to 2 years of experience in data science or machine learning, including internships or substantial academic projects. Solid foundations in statistics and machine learning for structured and unstructured data. Good Python skills and familiarity with the standard data science stack. Hands-on experience with embeddings and LLM-based solutions. Curiosity, a willingness to learn, and clear communication. Experience with temporal or geospatial data. Personal or academic projects involving agents, LLM fine-tuning, embeddings. Interest in marketing technology, ad tech, or audience modelling. Open-source contributions, publications, or competition results.

Условия:

Healthcare benefits Remote working Flexible working hours Impactful projects Continuous learning and development Satalia is home to some of the brightest minds in AI.

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.

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Good luck!