1 to 25 of 30 Logistic Regression Jobs

quality. Familiarity with advanced patterns such as GraphRAG and agentic RAG to reduce hallucination and improve factual grounding. Technical Proficiency Machine learning algorithms: linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing ...

than 2 yearsAbility to client face and consultIdeally a PhD masters okStrong understanding of probability and statisticsMachine learning (experience of techniques such as linear regression, logistic regression, boosting, kNN)PythonExperience of one or more common frameworks (e.g. Caffe, Theano, Torch, Tensorflow, scikit-learn)The environment is that ...

than 2 yearsAbility to client face and consultStrong Data Science backgroundStrong understanding of probability and statisticsIdeally Machine learning (experience of techniques such as linear regression, logistic regression, boosting, kNN)Ideally Python or another languageExperience of one or more common frameworks (e.g. Caffe, Theano, Torch, Tensorflow, scikit-learn ...

services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud ...

experience developing cloud‐based machine learning services using one or more cloud providers (preferably GCP). Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem ...

Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem ...

Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem ...

design, retrospective analysis, performance analysis, population split analysis and reject analysis. This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

design, retrospective analysis, performance analysis, population split analysis and reject analysis. This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

sample design, retrospective analysis, performance analysis, population split analysis and reject analysis.This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

sample design, retrospective analysis, performance analysis, population split analysis and reject analysis.This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

sample design, retrospective analysis, performance analysis, population split analysis and reject analysis.This position will involve performing analysis of multiple data sources using statistical analysis (Logistic Regression, Linear Regression, Decision Trees, Exploratory Data Analysis, CHAID analysis & Cluster Analysis) and computer science to solve business problems. We are looking ...

tools.Experience with advanced algorithms in deep learning, neural networks, reinforcement learning, and transfer learning.Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing.Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation ...

following: database query and management tools (SQL, Spark, Preseto/Athena/Hive/HQL etc.) Hands-on experience with advanced analytics like logistic regression, time series, forecasting, optimization, and other predictive modeling techniques. ML experience and knowledge of ML platforms, libraries and programming Experience using GLMs, XGBoost ...

DesiredArtificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Logistic Regression Model (Inactive), Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai (Inactive), Pandas (Python) (Inactive), Python (Programming Language ...

Python skills with a strong foundation in software and data engineering best practices. Deep knowledge of statistical and machine learning models—gradient boosted trees, logistic regression, neural networks, survival analysis, etc. Comprehensive understanding of statistics: hypothesis testing, confidence intervals, bootstrap. Experience with end-to-end model development ...

scripting/programming languages (R, Matlab, etc) Expertise in a broad range of data science/machine learning algorithms (Monte Carlo simulation, neural networks, logistic regression, random forest, etc.) with a proven track record of delivering solutions to complex problems. Ability to bring clarity to complex domains, rapidly ...

skills with good understanding of best practices in software engineering and data engineeringIn-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etcSolid knowledge of statistics: hypothesis testing, confidence intervals, bootstrapExperience of end-to-end model development and maintenance ...

skills with good understanding of best practices in software engineering and data engineeringIn-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etcSolid knowledge of statistics: hypothesis testing, confidence intervals, bootstrapExperience of end-to-end model development and maintenance ...

Toolkit Using gradient boosting (e.g. XGBoost, LightGBM, CatBoost) as the default for tabular prediction. Recognising when simpler, more interpretable models, such as regularised logistic regression or well‐constrained decision trees, are the better choice. Applying clustering and segmentation techniques (e.g. k‐means, hierarchical or sequence‐based clustering ...

reporting, early warning systems, customer segmentation and scoring, credit risk insights, or personalisation. • Strong understanding of AI and data science techniques, including statistical modelling, logistic regression, NLP, LLMs, Generative AI, and Agentic AI. • Strong track record of applying Agile product development methodologies. • Customer-centric mindset with a proven ...

reporting, early warning systems, customer segmentation and scoring, credit risk insights, or personalisation. • Strong understanding of AI and data science techniques, including statistical modelling, logistic regression, NLP, LLMs, Generative AI, and Agentic AI. • Strong track record of applying Agile product development methodologies. • Customer-centric mindset with a proven ...

reporting, early warning systems, customer segmentation and scoring, credit risk insights, or personalisation. - Strong understanding of AI and data science techniques, including statistical modelling, logistic regression, NLP, LLMs, Generative AI, and Agentic AI. - Strong track record of applying Agile product development methodologies. - Customer-centric mindset with a proven ...

Applied Machine Learning : Strong background in feature engineering, tabular machine learning, calibrated scoring systems, and production use of models such as gradient‐boosted trees, logistic regression, and related approaches. Content‐Aware Recommendation Systems : Experience combining embeddings, semantic similarity, collaborative signals, and content understanding to build recommendation systems that ...

Applied Machine Learning: Strong background in feature engineering, tabular machine learning, calibrated scoring systems, and production use of models such as gradient-boosted trees, logistic regression, and related approaches.Content-Aware Recommendation Systems: Experience combining embeddings, semantic similarity, collaborative signals, and content understanding to build recommendation systems that perform ...