13 of 13 Permanent Logistic Regression Jobs in London

with spatial-temporal data sets, with exposure to maritime data preferred Experienced in evaluating, training, and communicating the performance of ML models (e.g., supervised models, such as gradient boosting, logistic regressions etc. and non-supervised approaches, including clustering) Advise product stakeholders on feature and modelling accuracy and potential iterations which may drive improved model reliability and accuracy. Develop a More ❯

data scientist experience - Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab) - Experience with statistical models e.g. multinomial logistic regression - Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive) - Experience working with data engineers and business intelligence engineers collaboratively More ❯

AI/Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow or More ❯

projects, including survey, database, and hybrid segmentations using multiple data sources. Apply best practices in segmentation to produce high-quality, actionable insights for clients. Create segmentation models using multinomial logistic regression and linear discriminant analysis. Advanced Analytics Skills Strong working knowledge of analytical techniques such as conjoint analysis, machine learning (e.g., Random Forests, SVM), statistical methods (e.g., regression More ❯

techniques. Attention to detail and ability to work with large datasets accurately. Proficiency in Python or R (5+ years' experience). Knowledge of statistical models such as linear and logistic regression, t-tests, ANOVA. Experience collecting, organizing, and analyzing data from diverse sources. Strong analytical, problem-solving, and critical reasoning skills. Excellent communication skills, able to convey complex More ❯

and capable of working with large data sets and attention to accuracy and completeness. Proficiency utilising Python or R (5+ years' experience) Familiarity with conventional statistical models (linear/logistic regression, t-tests, ANOVA) Experience in collecting, organising, and analysing data from diverse sources. Strong analytical thinking, problem-solving, and critical reasoning skills. Excellent written and verbal communication More ❯

SQL and database management Experience with AWS services like Glue, Athena, Redshift, Lambda, S3 Python programming experience using data libraries like pandas and numpy etc Interest in machine learning, logistic regression and emerging solutions for data analytics You are comfortable working without direct supervision on outcomes that have a direct impact on the business You are curious about More ❯

research . You should: Be comfortable using and interpreting data to draw insights Have a basic understanding of key statistical techniques such as: Conjoint analysis MaxDiff Segmentation Linear or logistic regression Significance testing Be confident using Excel , PowerPoint , and Word Be open to learning tools such as: SPSS , Q , Sawtooth , Displayr , Crunch.io (experience with any of these is More ❯

research . You should: Be comfortable using and interpreting data to draw insights Have a basic understanding of key statistical techniques such as: Conjoint analysis MaxDiff Segmentation Linear or logistic regression Significance testing Be confident using Excel , PowerPoint , and Word Be open to learning tools such as: SPSS , Q , Sawtooth , Displayr , Crunch.io (experience with any of these is More ❯

Risk Modeller to join a consumer lending FinTech on a day rate contract basis. The role will include developing a PD Model and other Credit Models/Scorecards using logistic regression and gradient boosting methods. There will also be work/projects within business strategy, churn likelihood, potential for leaving and complexion models. The ideal candidate should have More ❯

Risk Modeller to join a consumer lending FinTech on a day rate contract basis. The role will include developing a PD Model and other Credit Models/Scorecards using logistic regression and gradient boosting methods. There will also be work/projects within business strategy, churn likelihood, potential for leaving and complexion models. The ideal candidate should have More ❯

maintain IFRS9 models: PD, LGD, and EAD models across various lending portfolios Design and build credit scorecards: Acquisition, behavioural, and collections scorecards using industry best practices (e.g. WOE binning, logistic regression) End-to-end model ownership: From data extraction and feature engineering to validation and deployment Collaborate cross-functionally: Work closely with credit risk, data engineering, product, and More ❯

maintain IFRS9 models: PD, LGD, and EAD models across various lending portfolios Design and build credit scorecards: Acquisition, behavioural, and collections scorecards using industry best practices (e.g. WOE binning, logistic regression) End-to-end model ownership: From data extraction and feature engineering to validation and deployment Collaborate cross-functionally: Work closely with credit risk, data engineering, product, and More ❯