Bachelor degree in Business, Economics, Statistics, Data Science, Data Mining, or similar quantitative field.
Proven successful and trackable experience in an analytical role or data scientist role involving extraction, analysis, and/or modeling.
Solid experiences in SQL, familiar with SQL functions such as window functions and aggregate functions.
Solid experiences in Python, familiar with data analysis libraries such as pandas, numpy, matplotlib, scikit-learn, etc.
Experience in using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analysing data, drawing conclusions, and developing actionable recommendations for business units.
Experience in developing production-grade ML systems including exploratory analysis, feature engineering, hyperparameter tuning, model training, model selection, creating data pipelines, etc.
Experience in working with deep learning frameworks such as PyTorch for real world problems.
Knowledge of Computer Science fundamentals such as object-oriented design, graph algorithm, algorithm design, data structures, problem solving and complexity analysis.
Self-driven, innovative, collaborative, with good communication and presentation skills, able to translate between business and technical audiences.