Data Scientist

Responsibilities

• Gather, clean, and analyze large and complex datasets from various sources.
• Build and deploy predictive and machine learning models (ML / DL) to solve real business challenges.
• Identify optimization opportunities and make data-driven recommendations.
• Design custom algorithms tailored to different business areas (marketing, product, operations, finance, etc.).
• Work closely with Data Engineers, Analysts, and Product Managers.
• Communicate findings through clear visualizations and reports that support strategic decisions.
• Stay up to date with the latest trends in data science, machine learning, and AI.

• Master’s degree (or higher) in statistics, applied mathematics, computer science, or a related field.
• At least 3 years of professional experience in applied data science.
• Strong proficiency in Python and libraries such as Pandas, Scikit-learn, Tensor Flow, PyTorch, etc.
• Solid knowledge of SQL and experience with data visualization tools (Matplotlib, Seaborn, Plotly, etc.).
• Proven experience in deploying models into production environments.
• Analytical mindset, scientific rigor, and the ability to translate technical results into business language.

• Familiarity with Big Data tools (Spark, Hadoop).
• Experience with cloud platforms (GCP, AWS, or Azure).
• Exposure to NLP, Computer Vision, or Time Series forecasting.
• Hands‑on with collaborative notebooks (Jupyter, Databricks).
• Knowledge in CI / CD practices and MLOps frameworks is a big plus.

• High‑impact projects that influence strategic decisions.
• A collaborative and innovation‑driven culture.
• Access to rich and diverse datasets.
• Continuous learning opportunities and attendance at tech / AI conferences.