visualization techniques and platforms. Applying statistics, machine learning, and analytical approaches Systems, Actuarial Sciences, Applied Mathematics, Statistics). Candidates without a Computer Science, Engineering theoretical predictive modelling, mathematical and statistical skills. Proficient in SQL. 5 years of experience advantageous. Highly analytical with strong maths and statistics skills. Experience using business intelligence
Analytics/Data • Science/Modelling/Statistics • Programming and statistical computer languages (R, Python management and organisational skills • Knowledge of statistical modelling and data mining techniques i.e. Regression network analysis etc. • Querying databases using statistical computer languages i.e. R, Python, SQL, • etc
degree in a relevant field (e.g., Mathematics, Statistics, Computer Science, Data
data queries. • Honours degree in Mathematical Statistics or Applied Mathematics. • Other postgraduate postgraduate qualifications with a numerical and statistical aspect and/or experience will be considered. • Min 4
degree in a relevant field (e.g., Mathematics, Statistics, Computer Science, Data Analytics/Science). Proven large datasets efficiently. Experience with statistical analysis techniques and data modelling. Excellent patterns, and relationships within the data. Apply statistical techniques and data visualization methods to
(RegEx). Comfortable with baseline statistics and interpreting statistical data. Intermediate or advanced
innovate. Requirements Degree in actuarial science, statistics, mathematics, or engineering Responsibilities
valuable information from large datasets. - Apply statistical techniques and hypothesis testing to validate hands-on experience with machine learning and statistical analysis. Proficiency in data analysis and modelling
information from large datasets