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Data Scientist
Satori Analytics. Work with stakeholders to understand business problems and contribute to solutions using machine learning and optimization .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining machine learning pipelines, with a strong foundation in statistical theory and algorithmic thinking. Proficient in Python programming and data analysis, with the ability to translate business needs into effective modeling practices.
Highest-signal resume keywords
Machine Learning Pipeline DevelopmentPython ProgrammingStatistical AnalysisData Exploration and VisualizationMLOps Familiarity
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ScienceStatistical TheoryAlgorithmic ThinkingExploratory Data AnalysisSupervised LearningUnsupervised LearningOptimizationPythonSQL
Soft Skills
CuriosityProblem-Solving
Tools & Technologies
PandasScikit-LearnXGBoostLightGBMCatBoostGitFastAPIDockerAzureMLflow
Certifications & Qualifications
STEM Bachelor’s DegreeMaster’s Degree in Statistics/Data Science/Operations Research
Industry Keywords
Data PlatformsCampaign MeasurementCustomer InsightsAI/ML InitiativesFinancial Services
Tech Stack
Tools & technologiesAzureCloudDockerPandasPythonPyTorchScikit-LearnSQL
About the role
Key responsibilities & impact- Work with stakeholders to understand business problems and contribute to solutions using machine learning and optimization
- Analyze messy data from various data sources
- Build robust supervised and unsupervised machine-learning pipelines with support and guidance from senior team members
- Maintain and improve existing machine-learning solutions
- Design, build, and operate scalable data platforms for marketing-services products of a global payments and financial-services leader
- Enable campaign measurement, customer insights, reporting, and AI/ML initiatives
- Partner with Product, Engineering, Data Science, and Business stakeholders
- Deliver secure, reliable, high-quality solutions at enterprise scale
Requirements
What you’ll need- STEM Bachelor’s degree from a reputable university
- Master’s degree in Statistics/Data Science/Operations Research or equivalent is a strong plus
- 1–3 years of experience in Data Science/ML roles
- Deep understanding of algorithmic thinking
- Ability to distinguish clean, efficient, maintainable Python code from poor-quality code and adopt best practices
- Understanding of SQL is a plus
- Good understanding of machine learning, with exposure to at least two real-world projects involving supervised, unsupervised, or reinforcement learning/optimization
- Ability to explore large, complex datasets before modeling, including EDA and plotting
- Solid grasp of probability and statistical theory, including random variables and distributions, conditional probability and Bayes’ Theorem, expected value, measures of dispersion, hypothesis testing, and p-values
- Ability to translate business requirements into clean modeling practices
- Curiosity and willingness to learn new methods, frameworks, and techniques
- Experience with pandas/polars, scikit-learn, and xgboost/lightgbm/catboost
- Knowledge of Git for version control
- Knowledge of uv for Python version and package management or PyTorch for building, training, and deploying DNNs is a plus
- Experience with FastAPI and Docker is nice to have
- Working cloud knowledge, preferably Azure, is nice to have
- Familiarity with MLOps tracking platforms such as MLflow is nice to have
Benefits
Comp & perks- Competitive salary – A rewarding package that reflects your skills and experience.
- Flexible working – Enjoy flexible hybrid model in our modern Athens office or work remotely from anywhere in European economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).
- Private insurance
- Training budget for certifications or courses from technology partners including Microsoft, AWS, Salesforce, and Databricks.
- Career growth opportunities
- Collaborative environment with talented, supportive people
- Social events and celebrations
- Exclusive employee benefits
- Modern tools and technology
- Workplace focused on employee ideas, contribution, and well-being