Requirements
- Higher education in a specific field: econometrics, quantitative methods, mathematics, computer science, or similar.
- Min. 1 year of experience as a Data Scientist/Data Analyst, working with large data sets and production data.
- Ability to work with data, identify common problems, design and implement workflows, and test them.
- Good knowledge of data processing tools (SQL, Pandas).
- Good knowledge of Python, including object-oriented programming.
- Good knowledge of English, including technical concepts.
- Good communication skills, ability to engage in dialogue with business, and present complex concepts.
- Knowledge of machine learning techniques and algorithms and their implementation in Python.
- Ability to work with code versioning tools (git).
Preferred:
- Experience in consulting/advisory/working for Various external clients, possibly internal (e.g., company analytics department) / experience in several industries.
- Experience in end-to-end projects: from design to implementation.
- Experience in the financial sector (banking, risk, AML).
Technology stack:
Open-source: Python, notebook experience (Jupyter, Zeppelin).
Libraries: Pandas, Numpy, Scikit-learn, Xgboost (Keras, PyTorch, TensorFlow, Optuna preferred).
Git.
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