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Forestry Jobs in Johannesburg

1 - 8 of 8
1 - 8 of 8
Search Results - Forestry Jobs in Johannesburg
Professional Career Services-Johannesburg-
Security, forestry & Medical sectors)  •  Achieving of sales targets  •  Self-driven and motivated by strong commissions Skills  •  5 + years experience in Sales & New Business Development  •  2-3 years experience in sales of IT Solutions/converged...
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Mayfly Agri (Pty) Ltd-Johannesburg-
with personnel from the Department of Agriculture, Forestry and Fisheries with regards to product registrations.  •  Attending CropLife meetings as well as liaising with relevant industry stakeholders. Please note that subsequent to the screening and shortlisting...
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Network Recruitment-Johannesburg-
machine learning techniques such as:  •  Supervised learning (Random Forest, XGBoost, CatBoost, and Neural Networks)  •  Unsupervised learning (clustering, isolation forests, and anomaly detection)  •  Manage model risk across the full model lifecycle, including...
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Network Recruitment-Johannesburg-
machine learning techniques such as:  •  Supervised learning (Random Forest, XGBoost, CatBoost, and Neural Networks)  •  Unsupervised learning (clustering, isolation forests, and anomaly detection)  •  Manage model risk across the full model lifecycle, including...
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Forestry jobs – More locations:

Mediro ICT Recruitment-Johannesburg-
Recovery methodologies and practice as well as Windows Clustering for server 2008 /2012 /2016.Integrate the server automation process either by custom scripts or via third-party solutions.Understanding of group policy, OU's forests and the use of Manage...
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wePlace-Johannesburg-
Supervised learning (Random Forest, XGBoost, CatBoost, Neural Networks)  •  Unsupervised learning (clustering, isolation forests)  •  Managing model risk across the end‑to‑end model lifecycle, including:  •  Feature engineering and data preparation  •  Model...
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Network Recruitment-Johannesburg-
XGBoost, CatBoost, Random Forest, and Neural Networks)  •  Unsupervised learning (clustering, anomaly detection, and isolation forests)  •  Manage the full model lifecycle:  •  Feature engineering and data preparation  •  Model training, evaluation...
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Network Recruitment-Johannesburg-
financial crime) models  •  Work hands-on with advanced ML techniques, including:  •  Ensemble methods (XGBoost, CatBoost, and Random Forest)  •  Neural networks  •  Clustering and anomaly detection models  •  Manage the full model lifecycle:  •  Data preparation...
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