11/04/2024 | Fulltime | Manchester | CV-Library | £30,000 - £40,000 / Year Valuations, liaising with different stakeholders and developing new opportunities. The ideal candidate will have previous experience working in a similar environment such as rural land, farming, forestry or renewable energy. The role would suit someone who is driven by progression and career development
Save for laterRegister your CV08/04/2024 | Fulltime | Manchester | CV-LibraryManchester or Gloucester and there will be an element of travel involved. Please see details for each of our locations below; Romsey Alongside hybrid and flexible working options, you’ll find our Romsey site located within beautiful Hampshire countryside, close to the picturesque New Forest District
Save for laterRegister your CV08/04/2024 | Fulltime | Manchester | CV-Library | £200 - £230 And a share code – link for this is below; About the school Received good and positive feedback from OFSTED ‘A wide range of well-chosen, effective, and stimulating strategies to develop learning in literacy and numeracy, together with the environmental learning provided by ‘Forest Schools’, drive pupils
Save for laterRegister your CV01/04/2024 | Fulltime | Manchester | CV-Library | £120 - £160 Qualification? TeacherActive is proud to be working with a national 100 place private day nursery in Manchester. The nursery is well sought-after, due to its outdoor forest area, and boasts an ‘outstanding’ OFSTED rating. The nursery focuses on providing exceptionally high standards of physical, emotional
Save for laterRegister your CV28/03/2024 | Fulltime | Manchester | CV-LibraryAnalysts Key Skills and Experience Experience in tuning and deploying machine learning methods Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, Clustering, Isolation Forest, SVMs, NLP
Save for laterRegister your CV28/03/2024 | Fulltime | Manchester | CV-LibraryProducts and/or pricing teams, including knowledge of current trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge
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