Satalia
51 - 200 employees
Founded 2010
🤖 Artificial Intelligence
🤝 B2B
🏢 Enterprise
💰 Grant on 2016-02
Artificial Intelligence • B2B • Enterprise
Satalia is a company that leverages advanced technologies to optimize and improve various business operations. They provide a platform for cloud development and data-driven services, employing cloud architects and data scientists to deliver innovative solutions. Satalia operates remotely, with locations in Greece, London, Kaunas, and Vienna. They focus on integrating analytics and marketing strategies to enhance user experience and functionality on their platforms.
Data Scientist – Mid Level
🕒 April 30
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Satalia
51 - 200 employees
Founded 2010
🤖 Artificial Intelligence
🤝 B2B
🏢 Enterprise
💰 Grant on 2016-02
Artificial Intelligence • B2B • Enterprise
Satalia is a company that leverages advanced technologies to optimize and improve various business operations. They provide a platform for cloud development and data-driven services, employing cloud architects and data scientists to deliver innovative solutions. Satalia operates remotely, with locations in Greece, London, Kaunas, and Vienna. They focus on integrating analytics and marketing strategies to enhance user experience and functionality on their platforms.
📋 Description
• Build and iterate on ML models — from data exploration and feature engineering through training, evaluation, and deployment • Implement and maintain components of production ML pipelines: data pre-processing, model serving, monitoring, and retraining workflows • Contribute to LLM-powered systems — building prompt chains, evaluation harnesses, RAG pipelines, or fine-tuning workflows • Analyse large multimodal datasets (text, image, video, structured metadata) to extract features and insights that feed downstream models • Write clean, tested, production-quality Python code — not just notebooks • Participate in code reviews, design discussions, and experiment retrospectives
🎯 Requirements
• 2–4 years of experience building ML models, with at least some of that work deployed to production • Solid fundamentals in machine learning: you understand bias-variance trade-offs, cross-validation, regularisation, and can reason about why a model is underperforming • Working proficiency in Python and comfort with core ML libraries • Exposure to at least one of: NLP/LLMs, computer vision, recommender systems, or time-series modelling • Strong experience with software engineering practices — Git, testing, CI/CD, code review • Curiosity about LLMs and modern AI tooling • Clear communication — you can explain your modelling choices and results to both technical and non-technical colleagues
🏖️ Benefits
• healthcare • Remote working - café, bedroom, beach - wherever works • Truly flexible working hours - school pick up, volunteering, gym • Generous Leave – holidays in line with Greek Law, plus bank holidays and enhanced family leave • Impactful projects - focus on bringing meaningful social and environmental change • People oriented culture - wellbeing is a priority, as is being a nice person • Transparent and open culture - you will be heard • Development - focus on bringing the best out of each other
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