parameter estimation, factors selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming. Experience with machine learning methods, such as regularization, random forests, neural networks and deep learning. Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus. Experienced in more »
give them and their clients a competitive edge. You will be working as part of a high performing team developing next gen models utilising randomforest and gradient boosting. You will need to have a background in consumer lending and strong technical skills including the likes of Python more »
and analysis libraries (e.g., pandas, numpy, jupyter, scikit-learn). Knowledge of machine learning and statistical methods (e.g. linear/logistic regression, decision trees, randomforest, unsupervised methods) is preferred. Ability to convey complex information through data visualisation. Ability to manage different responsibilities and adapt to changing business more »
user experience. As Senior Data Analyst, you will: Improve budgeting and forecasting systems through: Trend analysis and statistical modelling Methods like Linear Models and Random Forests Analyse large datasets by: Applying feature analysis Utilising Permutation Importance Implement machine learning methodologies: Utilise TensorFlow/keras Create and optimise neural networks. more »
