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, logisticregression, and other advanced analytic techniques Have good written communication skills, including the ability to describe statistical results to non-statistical more »
Familiarity with data manipulation and analysis libraries (e.g., pandas, numpy, jupyter, scikit-learn). Knowledge of machine learning and statistical methods (e.g. linear/logisticregression, decision trees, random forest, unsupervised methods) is preferred. Ability to convey complex information through data visualisation. Ability to manage different responsibilities and 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 logisticregression, significance testing, and statistical modelling. Educated to degree level in a numerate/analytical subject. Solutions focused approach, with an intellectual curious more »
Proficiency in data analysis, data mining, and statistical techniques Proficiency utilising Python or R (2+ years' experience) Familiarity with conventional statistical models (linear/logisticregression, t-tests, ANOVA) Experience in collecting, organizing, and analysing data from diverse sources Strong analytical thinking, problem-solving, and critical reasoning skills more »
project documentation, and system management Become familiar with all offerings outlined in the Insider's Guide to ACG various statistical offerings and methods (CHAID, logistic/multiple regression, cluster analysis, factor analysis) Epsilon data assets the SAS macro library Participate in the design, planning & execution of projects Effectively more »
