Data Scientist

Company:
Location: Queensland

*** Mention DataYoshi when applying ***

Location:
Queensland, Australia

Job Type:
Permanent

Discipline:
Data, AI & Analytics

Salary:
Negotiable

Contact:
Chelsea Gerrard

As the Data Scientist, you will work autonomously within a large Data & Analytics team to provide support of data heavy performance management systems, along with extensive programming experience across R, SQL and machine learning algorithms. You will have a thorough grasp of Multiple Regression, Principle Component Analysis and ML approaches (e.g. Elastic Net and Gradient Boosting.) You will also have exposure to non-numerical analysis (text, geospatial)

About the Role:

  • Support the generation of complex data driven insights to;
  • Improve outcomes for customers based on evidenced input-outcome relations;
  • Improve customer satisfaction and retention based on sound understanding of key drivers of behaviours and needs;
  • Improve workforce engagement and performance through understanding of performance drivers;
  • Improve commercial performance through identification of growth, market and efficiency opportunities;
  • Apply complex statistical and machine learning data science methods to identify relevant patterns in big unstructured data sets; and
  • Support the development of complex business models (e.g. pricing, economic scenarios, forecasting).

About You:

  • + years' experience as a data scientist in an advanced analytics team;
  • Extensive experience with modern coding languages (SQL and R is mandatory);
  • Expert knowledge and skills in advanced machine learning such as gradient boosting machines (GBM), random forest (RF) and elastic net general linear modelling (GLM);
  • Demonstrated experience with text analytics and or the applied use of geospatial data is desirable;
  • Experience with predictive analytics and complex business models (e.g. Scenarios, forecasting);
  • Exposure to or a desire to learn neural nets (NN); and
  • Degree in a data / analytics or related discipline and / or extensive experience using advanced modelling techniques in an applied setting.

As the Data Scientist, you will work autonomously within a large Data & Analytics team to provide support of data heavy performance management systems, along with extensive programming experience across R, SQL and machine learning algorithms. You will have a thorough grasp of Multiple Regression, Principle Component Analysis and ML approaches (e.g. Elastic Net and Gradient Boosting.) You will also have exposure to non-numerical analysis (text, geospatial)

About the Role:

  • Support the generation of complex data driven insights to;
  • Improve outcomes for customers based on evidenced input-outcome relations;
  • Improve customer satisfaction and retention based on sound understanding of key drivers of behaviours and needs;
  • Improve workforce engagement and performance through understanding of performance drivers;
  • Improve commercial performance through identification of growth, market and efficiency opportunities;
  • Apply complex statistical and machine learning data science methods to identify relevant patterns in big unstructured data sets; and
  • Support the development of complex business models (e.g. pricing, economic scenarios, forecasting).

About You:

  • + years' experience as a data scientist in an advanced analytics team;
  • Extensive experience with modern coding languages (SQL and R is mandatory);
  • Expert knowledge and skills in advanced machine learning such as gradient boosting machines (GBM), random forest (RF) and elastic net general linear modelling (GLM);
  • Demonstrated experience with text analytics and or the applied use of geospatial data is desirable;
  • Experience with predictive analytics and complex business models (e.g. Scenarios, forecasting);
  • Exposure to or a desire to learn neural nets (NN); and
  • Degree in a data / analytics or related discipline and / or extensive experience using advanced modelling techniques in an applied setting.

*** Mention DataYoshi when applying ***

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