1 to 8 of 8 Logistic Regression Jobs

statistical methods applied to data analysis Have user experience of R, Python or equivalent analytic software. Have understanding of various statistical methodologies including linear regression, logistic regression, and other advanced analytic techniques Have good written communication skills, including the ability to describe statistical results to non-statistical more »

cloud platform (GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. Proven knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning more »

cloud platform (GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. Proven knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning more »

in insurance pricing or related analytical background. Proficiency in programming languages such as SAS, R, Matlab, or Python. Experience with predictive modelling techniques like Logistic Regression, Decision Trees, Random Forests, etc. Familiarity with Emblem and Radar. Strong communication skills to convey statistical concepts to non-statistical audiences. Self more »

or related analytical background. Highly skilled in the use of programming language e.g. SAS Experience in some of the following predictive modelling techniques e.g. Logistic regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets. Experience of Emblem and more »

this page KEYWORDS: Credit Risk Analytics, Credit Risk Models, Impairment, Capital, Basel, AIRB, Scorecards, Decision Science, Stress Testing, SAL, SQL, PD, LGD, EAD, IFRS9, Logistic Regression, Decision Tree, Probability of Default, Exposure of Default, Loss Given Default more »

updating of an analysis workplan. Requiring adjustment due to fluctuating workload, prioritising unpredictable and conflicting demands. Use statistical and mathematical modelling techniques such as logistic regression and simulation to inform analysis. Contribute to research papers, research proposals and policies on an ongoing basis. Perform within an environment where more »

testing and measurement strategies such as Geo-testing and marketing attribution. You are an expert in using various analysis techniques, such as linear and logistic regression, significance testing, and statistical modelling. Educated to degree level in a numerate/analytical subject. Solutions focused approach, with an intellectual curious more »