26 to 50 of 65 Permanent Logistic Regression Jobs

performing statistical analyses leading to the understanding of the structure of data sets. Proven and demonstrable experience with at least three of the following machine learning algorithms: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. Experience working with Java and Python, and strong understanding of data More ❯

AI/Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow or More ❯

effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering, Principal Component Analysis, Market Basket analysis). Experience in solving optimization problems like inventory and network optimization. Should have hands on More ❯

Proficiency: Strong skills with libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Ability to write clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering (k-means, DBSCAN), and time-series forecasting (ARIMA, Prophet). Model evaluation, tuning, and deployment. Business Requirement More ❯

e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.). 5+ years of data scientist experience. Experience with statistical models e.g., multinomial logistic regression. Experience working collaboratively with data engineers and business intelligence engineers. Experience managing data pipelines. Experience as a leader and mentor on a data science team. #J-18808-Ljbffr More ❯

of experimentation methodologies (A/B testing, multivariate testing, etc.) and their application in product decision-making. In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc. Experience with end-to-end model development and maintenance of ML models used for business-critical decisions. Solid understanding of key product … you built or launched AI or ML-powered products in a professional setting? * Select... Which statistical or machine learning models have you worked with extensively? (Select all that apply) * Logistic Regression Survival Analysis Other Have you worked in or supported a product related to search or discovery (e.g., eCommerce search engines, recommender systems)? * Select... #J-18808-Ljbffr 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

decisions to drive business performance and improve customer experience. In your role as Senior Data Scientist you’ll utilise our data science capability to predict likelihood to convert. Build logistic regression and machine learning models. help deliver a data driven omni-channel communication strategy, systemic comms sent to the right customers, for the right reasons at the right … what we are looking for: Proven experience in Data Science, preferably in a start-up or fast-paced environment and/or within Financial Services. Build new propensity models (regression/machine learning) to enable us to grow the number of products our customers have with us, increase their balance and to retain more customers Enhance our 600-attribute 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 ❯

Mathematics, Statistics, Data Science, Economics, or Physics 1 to 2 years of experience in a Financial data driven environment, or strong academic project experience Familiarity with modelling techniques like logistic regression or basic machine learning A keen interest in data science and its applications in finance or risk Strong attention to detail and a problem solving mindset A More ❯

Mathematics, Statistics, Data Science, Economics, or Physics 1 to 2 years of experience in a Financial data driven environment, or strong academic project experience Familiarity with modelling techniques like logistic regression or basic machine learning A keen interest in data science and its applications in finance or risk Strong attention to detail and a problem solving mindset A More ❯

Mathematics, Statistics, Data Science, Economics, or Physics 1 to 2 years of experience in a financial data -driven environment or strong academic project experience Familiarity with modelling techniques like logistic regression or basic machine learning A keen interest in data science and its applications in finance or risk Strong attention to detail and a problem-solving mindset A More ❯

of Logic Apps, Power Apps, and Azure Cognitive Services and similar are a nice to have. Knowledge of Machine Learning algorithms and their practical applications, such as Decision Trees, Logistic Regression, Neural Networks, and Genetic Algorithms. Other skills such as Visual Studio, GIT source control, SSIS, Rest/SOAP Integration and MDX will be an advantage as will More ❯

as is a general willingness to constantly learn and improve one's technical skill set. This role also requires the ability to conduct statistical modeling (such as linear and logistic regression) in order to inform divisional strategy, and work with non-technical stakeholders to understand key questions and problems and use a variety of approaches to address them More ❯

Gen AI within their organisation and are looking to utilise the newest technologies on the market. Key Responsibilities: Design and implement machine learning models for both supervised (e.g., classification, regression) and unsupervised learning tasks. Manage the full model development lifecycle, including data preparation, exploratory analysis, model training, validation, and deployment. Develop and fine-tune predictive algorithms such as: Classification … Logistic Regression, Decision Trees, Random Forests. Regression: Linear Models, Gradient Boosting, Neural Networks, K-Nearest Neighbors. Build models for customer behavior prediction and risk assessment in insurance, particularly in underwriting and claims. Apply natural language processing (NLP) for tasks like document classification and information extraction using OCR. Utilize cloud-based platforms like AWS SageMaker and Databricks for More ❯

Gen AI within their organisation and are looking to utilise the newest technologies on the market. Key Responsibilities: Design and implement machine learning models for both supervised (e.g., classification, regression) and unsupervised learning tasks. Manage the full model development lifecycle, including data preparation, exploratory analysis, model training, validation, and deployment. Develop and fine-tune predictive algorithms such as: Classification … Logistic Regression, Decision Trees, Random Forests. Regression: Linear Models, Gradient Boosting, Neural Networks, K-Nearest Neighbors. Build models for customer behavior prediction and risk assessment in insurance, particularly in underwriting and claims. Apply natural language processing (NLP) for tasks like document classification and information extraction using OCR. Utilize cloud-based platforms like AWS SageMaker and Databricks for More ❯