15 of 15 Permanent Logistic Regression Jobs

/bad definitions Engineering characteristics and treating missing and special values Performing monotonic binning, Weight of Evidence and Information Value analysis Developing an interpretable logistic-regression scorecard Completing feature selection, model tuning and points-based score scaling Validating the model using measures such as Gini … Python experience within credit-risk modelling Strong SQL skills and the ability to prepare complex modelling datasets independently Practical experience with WoE, IV, binning, logistic regression and score scaling Experience defining modelling samples, performance windows and credit outcomes A track record of implementing scorecards within lending, underwriting, collections ...

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 ...

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 ...

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 ...

with commercial impact. You'll be responsible for: Developing acquisition and behavioural credit scorecards using CRA data Building statistical and machine learning models including logistic and linear regression Designing and implementing credit strategies for new and existing customer portfolios Analysing large datasets using SQL and Python … Credit risk experience across model development or strategy Strong SQL skills alongside Python or SAS (Python preferred) Experience with statistical modelling techniques such as logistic regression or machine learning Excellent communication skills with the ability to present to clients and senior stakeholders THE BENEFITS ...

with commercial impact. You'll be responsible for: Developing acquisition and behavioural credit scorecards using CRA data Building statistical and machine learning models including logistic and linear regression Designing and implementing credit strategies for new and existing customer portfolios Analysing large datasets using SQL and Python … Credit risk experience across model development or strategy Strong SQL skills alongside Python or SAS (Python preferred) Experience with statistical modelling techniques such as logistic regression or machine learning Excellent communication skills with the ability to present to clients and senior stakeholders THE BENEFITS ...

postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development ...

best practices Key Skills and Experience: Previous experience in tuning and deploying machine learning methods 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 DevOps and Azure ML, or other MLOps ...

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. ...

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. ...

multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering, classification), correctly interpreting outputs and translating findings into actionable recommendations. Develop clear, audience-appropriate data visualisations and narratives that communicate insights to both … varied analytical techniques Advanced proficiency in SQL, Python, or R for data extraction, transformation, and visualisation at scale Proficient understanding of statistical concepts including regression, ANOVA, probability, and frequentist vs. Bayesian approaches, with the ability to distinguish statistically significant results from exploratory analysis Experience applying a range of modelling ...

multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering, classification), correctly interpreting outputs and translating findings into actionable recommendations. Develop clear, audience-appropriate data visualisations and narratives that communicate insights to both … varied analytical techniques Advanced proficiency in SQL, Python, or R for data extraction, transformation, and visualisation at scale Proficient understanding of statistical concepts including regression, ANOVA, probability, and frequentist vs. Bayesian approaches, with the ability to distinguish statistically significant results from exploratory analysis Experience applying a range of modelling ...

comfortably in notebooks, but can also write a plain .py script that runs on a schedule Familiar with scikit-learn or stats models for regression and forecasting Statistics and modelling Solid descriptive statistics, and the judgement to know when the mean is misleading Understands sampling, bias, correlation vs causation … confidence intervals Can run and interpret a hypothesis test or an A/B comparison Linear and logistic regression — fit one, and explain what the coefficients mean in plain English Knows when not to model, and will say “the data can't answer that” Other Data Skills ● Apply ...