We are seeking a Data Scientist with strong quantitative thinking and hands-on modeling ability to transform data into reliable analytical and predictive systems:
- Solid grounding in Mathematics and Statistics (linear algebra, probability, inference, optimization)Experience with end-to-end data workflows: data processing, exploration, feature design, and validation
- Practical experience in building ML models for prediction and pattern discovery (regression, classification, clustering)
- Understanding of model robustness: cross-validation, error analysis, and metric-driven evaluation
- Familiarity with tree-based models (Random Forest, Gradient Boosting) and regularization techniques
- Basic knowledge of neural networks; exposure to PyTorch or TensorFlow preferred
- Experience handling structured datasets and temporal/sequential data
- Strong proficiency in Python and data ecosystem tools (pandas, NumPy, scikit-learn)
- Ability to synthesize insights from data and communicate findings clearly and concisely
- Strong problem-solving mindset with attention to data integrity and modeling assumptions