7 of 7 Logistic Regression Jobs

Seaborn) Statistical & Multivariate Analysis Big Data: Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark DataLake Architecture, AWS Redshift, Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost Unsupervised Models: K-Means, DBSCAN, Hierarchical ...

experiment, engineer, and deliver innovative predictive models into our modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when … discovering good responsible actors and highlighting potential risks from others. Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such ...

days a year. Preferred Qualifications: Operational experience is preferred over manufacturing or production, but all candidates will be considered. Understanding of Linear/Logistic Regression, Decision Trees, Random Forest boosting algorithms. Experience with technical writing skills and the ability to communicate complex data in a simple and actionable ...

from "zero-shot" implementations to data-driven optimization. You will instrument data collection, design online evaluation metrics, and deploy simple, effective ML models (e.g., logistic regression, boosted trees) to optimize user outcomes based on real feedback. Be a "Full Stack" Partner: While the backend/data is your ...

from "zero-shot" implementations to data-driven optimization. You will instrument data collection, design online evaluation metrics, and deploy simple, effective ML models (e.g., logistic regression, boosted trees) to optimize user outcomes based on real feedback. Be a "Full Stack" Partner: While the backend/data is your ...

from \"zero-shot\" implementations to data-driven optimization. You will instrument data collection, design online evaluation metrics, and deploy simple, effective ML models (e.g., logistic regression, boosted trees) to optimize user outcomes based on real feedback. Be a \"Full Stack\" Partner: While the backend/data is your ...

experiment, engineer, and deliver innovative predictive models into our modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when … discovering good responsible actors and highlighting potential risks from others. Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such ...