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Satori Analytics is a fast-growing scale-up of 100+ tech specialists delivering innovative analytics solutions across industries including FMCG, retail, manufacturing, and financial services. The company brings clarity to global brands through data and AI, covering the entire data lifecycle from ingestion to AI applications.
As a Senior Data Scientist, you will design, build, and operate scalable data platforms for a global payments and financial-services leader's marketing services products. Your work will enable campaign measurement, customer insights, reporting, and AI/ML initiatives. You'll partner closely with Product, Engineering, Data Science, and Business stakeholders to translate complex data challenges into secure, reliable, high-quality solutions at enterprise scale.
Your responsibilities include:
- Define business problems and translate them into data science solutions
- Collect, clean, and analyze large datasets from various sources
- Develop and optimize machine learning and statistical models
- Build robust Supervised/Unsupervised ML pipelines with guidance from senior team members
- Maintain and improve existing ML solutions
- Communicate analytical findings and recommendations to stakeholders
- Work with stakeholders to understand business problems and contribute to ML/Optimization approaches
- Perform exploratory data analysis on messy, complex datasets
The role offers a hybrid work model with flexibility to work from the Athens office or remotely from anywhere in the European Economic Area (EU, Switzerland) or UK, up to 6 weeks per year. Benefits include competitive salary, training budget from top tech partners (Microsoft, AWS, Salesforce, Databricks), private insurance, and top-tier tech gear.
REQUIREMENTS:
- STEM Bachelor's degree from a reputable university; Master's degree in Statistics, Data Science, or Operations Research is a strong plus
- 3+ years of experience in Data Science/ML roles
- Deep understanding of algorithmic thinking and Python; ability to write clean, efficient, maintainable code and adopt best practices; SQL knowledge is a plus
- Good understanding of ML with exposure to at least two real-world projects involving Supervised, Unsupervised, or Reinforcement Learning/Optimization
- Ability to explore large, complex datasets through EDA and plotting
- Solid grasp of basic probability and statistical theory (random variables, distributions, conditional probability, Bayes' Theorem, expected value, hypothesis testing, p-values)
- Business acumen to translate business requirements into clean modeling practices; understanding that simplest solutions are often best
- Curious and willing to learn new methods, frameworks, and techniques
- Proficiency with pandas/polars, scikit-learn, xgboost/lightgbm/catboost; knowledge of git, UV, or PyTorch is a plus
NICE TO HAVES:
- Experience with FastAPI and Docker for building ML-centric applications
- Working cloud knowledge, preferably Azure
- Familiarity with MLOps tracking platforms like MLflow
