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Data Scientist
This job description is written in English, the working language for this role.
About the role
As a Data Scientist, you will be responsible for transforming large volumes of data into meaningful business insights through advanced analytics, statistical modeling, and machine learning techniques. You will collaborate with business stakeholders, Data Analysts, and Data Engineers to identify analytical opportunities, develop reliable models, and evaluate their performance. This role requires strong expertise in Python, SQL, statistical analysis, and machine learning, along with the ability to translate technical findings into practical business recommendations.
What you’ll do
- Collect, process, clean, and analyze structured and unstructured datasets from multiple data sources to support business analysis and model development.
- Perform Exploratory Data Analysis (EDA), statistical testing, feature engineering, and data transformation to identify meaningful patterns and relationships.
- Evaluate model accuracy and performance using appropriate metrics such as precision, recall, F1-score, RMSE, and AUC-ROC based on analytical requirements.
- Collaborate with business stakeholders to identify analytical requirements, define business problems, and translate them into measurable data science solutions.
- Develop, train, validate, and optimize machine learning models for predictive analytics, classification, regression, clustering, and other business use cases.
- Work closely with Data Engineers to ensure data availability, quality, and consistency throughout the analytical and model development processes.
What you’ll bring
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
- Minimum 3+ years of experience in Data Science, Machine Learning, Predictive Analytics, or a related analytical role.
- Strong proficiency in Python and SQL for data processing, statistical analysis, and machine learning development.
- Hands-on experience with data science libraries and frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Experience using data visualization tools such as Matplotlib, Seaborn, Plotly, Power BI, or Tableau.
- Familiarity with cloud-based machine learning platforms such as AWS SageMaker, Azure Machine Learning, or Google Vertex AI is an advantage.
Skills
Python & SQLStatistical Analysis & Hypothesis TestingExploratory Data Analysis (EDA)Scikit-learn / TensorFlow / PyTorchBusiness Insight Generation