Senior Research Data Scientist

Candidates should possess a degree or equivalent in a statistical or mathematical subject, and a minimum of 5 to 7 years of experience in Data Science. A strong understanding of statistics and mathematical methodologies, including forecasting, regression, linear models, time series, hypothesis tests, and optimization is required. Proficiency in Python and Spark for prototyping solutions and algorithm development on large datasets is also necessary, along with knowledge of machine learning techniques for classification, prediction, and clustering. Experience with experimental design methodology, databases (SQL and non-relational models), and algorithms such as Ancova, linear models with regularization, clustering, random forests, and xgboost is expected. Familiarity with Object-Oriented Programming and the ability to quickly learn open-source statistics and machine learning packages (Pandas, SciPy, Scikit-learn, TensorFlow) are also required.