10 of 10 Logistic Regression Jobs in the North West

true to our Customers, Owners and Colleagues alike. Essential Experience: Extensive experience designing, developing and deploying machine learning and AI solutions in production environments Statistical modelling, machine learning (e.g. logistic regression, random forest, XGBoost, and modern deep learning techniques (e.g. transformers, transfer learning, reinforcement learning) Proven ability to lead technical direction across projects or domains Expertise in model More ❯

for deployment, monitoring, and scaling of models. Qualifications Proven experience as a Machine Learning Engineer, with leadership experience in deploying models in production. Experience with classical ML algorithms (e.g., Logistic Regression, Random Forest, XGBoost), NLP, Transfer Learning, Deep Learning (e.g., BERT, Llama, LLMs). Expertise in end-to-end ML development and applications involving LLMs and frameworks like More ❯

decisions and strategic changes to prices to meet budget requirements. Key Skills and Experience: Previous experience within general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL More ❯

the wider piece, and identify where they can be improved Key Skills and Experience: Previous experience within general insurance 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 Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL More ❯

vision and long-term goals of the company. Key Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL More ❯

vision and long-term goals of the company. Key Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL More ❯

general insurance products 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 of the technical differences between different packages for some of these model types More ❯

long-term strategy and growth objectives Key Skills And Experience Substantial experience within Personal Lines Pricing, ideally including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance More ❯

long-term strategy and growth objectives Key Skills and Experience Substantial experience within Personal Lines Pricing, ideally including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance More ❯

long-term strategy and growth objectives Key Skills and Experience Substantial experience within Personal Lines Pricing, ideally including team or project leadership Proficiency in predictive modelling techniques such as Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets, and Clustering Strong skills in R, Python, PySpark, SAS, or SQL Proven ability to interpret performance More ❯