6 of 6 Logistic Regression Jobs

will be responsible for developing, leveraging and implementing out-of-box models of advanced statistical, descriptive, and predictive models (machine learning, supervised, unsupervised, classification, regression, and time series) for business needs. This position analyzes, proposes, and generates predictive and descriptive insights to create business opportunities. This role entails deep … improvement and recommend solutions based on data analysis Analytics and Predictive Modeling Build statistical, descriptive and predictive models using statistical techniques, such as logistic regression, clustering, principal components analysis, decision trees, correlation analysis, etc., looking to understand patterns, predict behavior, customer profiles, forecasting, among other challenges, with ...

validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such ...

validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such ...

postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development ...

datasets. Experience working within credit risk, fraud analytics, payments risk, or a related quantitative environment. Practical experience building supervised machine learning models such as logistic regression and gradient boosting models. Ability to work autonomously, solve problems proactively, and thrive in a fast-moving environment. Exposure to clustering, anomaly ...

services) Expertise: Solid understanding of computer science fundamentals and time-series forecasting Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning) Machine Learning Engineer, XGBoost, GCP, Python, SQL, time-series forecasting Reasonable Adjustments: Respect and equality ...