18 of 18 Logistic Regression Jobs

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 ...

Role Mandate: Lead the full scorecard lifecycle , from development and validation of logistic regression models through to implementation, testing and automated monitoring Own credit policy and credit reference agency analytics , incorporating FCA/governance requirements and leading senior stakeholder engagement. Ideal candidate Proven modelling/scorecard lead with … strong project delivery, transformation and stakeholder skills Must have Large scale analytics experience such as in a Banking/Telco environment SAS coding including logistic regression and macro proficiency Scorecard development and policy rule , experience across large portfolios Strategy development , implementation and testing skills Monitoring, development and automation ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...