Data Scientist job opportunity at Satori Analytics.

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Date2025-08-06T14:38:57.553Z bot
Satori Analytics Data Scientist
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Pattern: Full-time
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loacation Athens, Greece
loacation Athens....Greece
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Are you passionate about AI? 🤖 At Satori Analytics, we aim to change the world one algorithm at a time by bringing clarity to global brands thought Data & AI. From cloud-based ecosystems for fintech to predictive models for airlines, our cutting-edge solutions cover the entire data lifecycle—from ingestion to AI applications. As a fast-growing scale-up, our team of 100+ tech specialists—including Data Engineers, Data Scientists, and more—delivers innovative analytics solutions across industries like FMCG, retail, manufacturing and FSI. Join us as we lead the data revolution in South-Eastern Europe and beyond! What Your Day Might Look Like: Dive into diverse data sources, analyse them, and assess their impact on business outcomes. Build and optimise Data Science pipelines—balancing performance, business needs, and model complexity. Design and maintain ML pipelines: from data cleaning and transformation to model evaluation, hyperparameter tuning, and deployment. Research emerging technologies, platforms, and industry best practices to spot opportunities for innovation. Contribute to the evolution of our Data Analytics platform, especially in Machine Learning and MLOps capabilities. Your Superpowers 🚀: Proven Impact: Delivered at least two real-world ML projects in areas like: Recommender systems, Churn prediction & customer lifetime value modeling, Time series forecasting, Optimization (resource allocation, pricing, A/B testing), Customer segmentation & clustering Education: Bachelor’s degree in Mathematics, Computer Science, Electrical Engineering, Physics, or a related field—plus a Master’s in Data Science. Languages & Tools: Strong Python and SQL skills (R a plus), with hands-on experience in scikit-learn, pandas, NumPy, and Jupyter Notebooks. Visualization & Analysis: Proficient in EDA and feature engineering with tools like seaborn, plotly, and yellowbrick. ML Expertise: Solid grasp of machine learning algorithms (classification, regression, clustering, Bayesian learning, ensemble models), feature importance, and model explainability. Deep Learning: Familiarity with TensorFlow, PyTorch, Keras, or similar frameworks. Bonus Points for: Experience with Git/GitHub (or GitLab) and collaborative dev workflows. Exposure to MLOps platforms and tools. Use of AI-assisted development tools (like GitHub Copilot) to boost productivity and code quality.

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