1 to 25 of 27 Permanent Logistic Regression Jobs

basic/routine predictive models and algorithms with some complexity Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting. Analyze and interpret results with some complexity Exercise limited judgment and discretion within defined … analysis Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering Technical writing skills Strong communication and data storytelling presentation skills of technical material Ability to collaborate and build relationships Desired: Bachelor More ❯

basic/routine predictive models and algorithms with some complexity Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting. Analyze and interpret results with some complexity Exercise limited judgment and discretion within defined … analysis Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering Technical writing skills Strong communication and data storytelling presentation skills of technical material Ability to collaborate and build relationships Desired: Bachelor More ❯

quantitative subject (e.g. computer science, mathematics, engineering, science, economics or finance). A good understanding of statistical modelling knowledge or any machine learning technique knowledge (such as hypothesis testing, regression, logistic regression, random forest, etc.) Good stakeholder management experience. Comfortable presenting to senior leadership and C-suite. Experience in conducting A/B testing experimentation Strong experience More ❯

text data. Perform topic modeling, information extraction, sentiment analysis, summarization, and other types of text analytics to uncover insights. Develop and interpret multivariate statistical models, such as linear or logistic regression, survival analysis, and other parametric or non-parametric models that predict business metrics. Build machine learning pipelines to aid with decision-making and streamline critical business processes. … statistical programming experience with Python and SQL Experience working with large datasets, text data, and complex relational data models Strong understanding of various statistical methods, such as linear and logistic regression, time series, design of experiments, etc. Experience and creativity to come up with novel approaches to challenging problems Exceptional oral and written communication skills Ability to multitask More ❯

in healthcare or similar complex domains. Knowledge of statistical concepts and data mining methods such as: Hypothesis testing (or A/B testing), distribution analysis, Bayesian estimation, Linear and Logistic Regression, GLMs, text mining, time series analysis, etc. Knowledge of a variety of traditional machine learning techniques such as: feature engineering methods for large scale numerical and categorical More ❯

in healthcare or similar complex domains. Knowledge of statistical concepts and data mining methods such as: Hypothesis testing (or A/B testing), distribution analysis, Bayesian estimation, Linear and Logistic Regression, GLMs, text mining, time series analysis, etc. Knowledge of a variety of traditional machine learning techniques such as: feature engineering methods for large scale numerical and categorical More ❯

testing, benchmarking, and other robust model testing. Extensive Experience with at least three of the following statistical, econometric, data science, and predictive modeling approaches: Unsupervised Learning; K-Means; Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge More ❯

testing, benchmarking, and other robust model testing. Extensive Experience with at least three of the following statistical, econometric, data science, and predictive modeling approaches: Unsupervised Learning; K-Means; Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge More ❯

testing, benchmarking, and other robust model testing. Extensive Experience with at least three of the following statistical, econometric, data science, and predictive modeling approaches: Unsupervised Learning; K-Means; Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge More ❯

business insights and support strategic decision-making. Design and apply advanced predictive and machine learning models; including clustering (K-means, hierarchical), classification (KNN, Naive Bayes, CART), time series forecasting, logistic regression, and econometric models to optimize pricing strategies, assess price elasticity, segment customers, and enhance revenue across channels. Leverage generative AI and large language models (LLMs) to develop More ❯

of work experience with a PhD •With a track record of successfully delivering complex software systems or services as Senior Data Scientist •Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks. •Ability to program in one or more scripting languages such as Perl or Python and one or more programming More ❯

of work experience with a PhD •With a track record of successfully delivering complex software systems or services as Senior Data Scientist •Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks. •Ability to program in one or more scripting languages such as Perl or Python and one or more programming More ❯

e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 5+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression - Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ More ❯

practices within the organization Bonus Points Passion about online communities, games, and Twitch Experience working with software development and operational event data Experience with machine learning methods such as logistic regression, decision trees, and neural networks Perks Medical, Dental, Vision & Disability Insurance 401(k) Maternity & Parental Leave Flexible PTO Amazon Employee Discount Pursuant to the San Francisco Fair More ❯

practices within the organization Bonus Points Passion about online communities, games, and Twitch Experience working with software development and operational event data Experience with machine learning methods such as logistic regression, decision trees, and neural networks Perks Medical, Dental, Vision & Disability Insurance 401(k) Maternity & Parental Leave Flexible PTO Amazon Employee Discount Pursuant to the San Francisco Fair More ❯

motivated in data-driven security research; Expertise in DNS and DNS security; Good knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Trees, Logistic Regression, Deep Learning, and Boosting; Familiar with large-language models (LLMs) and experience to leverage them to address cybersecurity threats; Excellent programming skills in Python, Shell script, Go More ❯

e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 4+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression PREFERRED QUALIFICATIONS - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience - Experience managing data pipelines Amazon is an equal opportunity employer and does More ❯

Learning, Data Mining, Statistics, or related technical field with preferred 3+ years of relevant experience Deep knowledge and experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc. Working knowledge in one or more of the following: generative AI, data mining, information retrieval, advanced statistics or natural language processing, computer vision More ❯

and who have the will to change it. Technical Skills: Proficiency in the modern machine learning techniques, such as Model Evaluation and Validation, Deep Learning and Time Series Analysis, Logistic Regression, Naive Bayes, Random Forest Models Self Starter: Confidence to prioritize work and delivery demonstrable results on a tight cadence. Domain Knowledge: Demonstrated experience or understanding of the More ❯

preferable in a Sciences major such as Statistics, Mathematics, Computer Science, Data Science, Operation Research or equivalent areas. Hands-on experience with standard statistical methods such as linear and logistic regression, SVM, confidence intervals, and significance testing, along with expertise in causal inference analysis. Expertise in writing custom SQL and experience with database design; Knowledge of a scripting More ❯

experience with real data for customer insights, business and market analysis will be advantageous. Experience with text analytics, data mining and social media analytics. Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc. More ❯

of the data science lifecycle. Proficiency in Python (or R), SQL, and experience with notebooks, Git workflows, and Power BI. Working knowledge of supervised machine learning (e.g., gradient boosting, logistic regression), evaluation metrics, and experiment design. Exposure to MLOps concepts, cloud platforms (e.g., Azure), and GenAI tools is a strong plus. Structured thinking, strong problem-solving, and clear More ❯

of the data science lifecycle. Proficiency in Python (or R), SQL, and experience with notebooks, Git workflows, and Power BI. Working knowledge of supervised machine learning (e.g., gradient boosting, logistic regression), evaluation metrics, and experiment design. Exposure to MLOps concepts, cloud platforms (e.g., Azure), and GenAI tools is a strong plus. Structured thinking, strong problem-solving, and clear More ❯

data using our ML platform to build features, train models, and deploy them to production. We use a combination of highly scalable and explainable models such as linear/logistic regression and random forests, along with the latest deep neural networks from transformers to LLMs. Some of our latest innovations have been around figuring out how best to More ❯

questions and developing hypotheses, and can collaborate with non-Data Scientists to clarify assumptions and influence decisions. You have extensive experience using various analysis techniques, such as linear and logistic regression, significance testing, and statistical modeling. You have a keen interest in using AI tools to support data exploration and analysis, and already have some experience in doing More ❯