5 of 5 Logistic Regression Jobs

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 ...

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 visualizations 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 ...

consultants on analytic client engagements involving descriptive, predictive, and prescriptive analysis through the consumer lending portfolio lifecycle, leveraging a variety of techniques (e.g., segmentation, logistic regression, etc). You will deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers. You will design ...

contract with strong likelihood of extension (or potential permanent conversion). Key Responsibilities Develop and deploy ML models for loan/deal scoring (classification, regression, ranking) Analyse financial, credit, and time-series data to extract predictive signals Build and benchmark models such as: Gradient boosting (XGBoost, LightGBM, CatBoost) Random … Forests Logistic/linear regression Design LLM-powered workflows for: Document understanding (loan docs, credit memos, financials) Risk factor extraction Deal-level reasoning and recommendations Combine structured ML outputs with LLM-based reasoning to deliver explainable scores Work closely with stakeholders to translate credit policy into data-driven ...