and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, randomforest), design of clinical trials. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal More ❯
of applying NLP expertise is of crucial importance to this hire. Head of Data Science : - Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, Random Forests, etc. - Experience with common data science toolkits, such as Python - Proficiency in using query languages such as SQL on a big data platform e.g. Hadoop, Hive - Good applied More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Gerrard White Consulting
the risk models and working closely with underwriting and technical modelling teams. ✔️ Personal Lines Pricing experience (Motor, Home or Pet) ✔️ Strong skills in predictive modelling – e.g., GLMs, GBMs, GAMs, Random Forests ✔️ Proficiency in R, Python, PySpark, SAS or SQL ✔️ Experience with Radar and/or Emblem ✔️ A numerate degree (e.g., Maths, Stats, Actuarial, Engineering) ✔️ Strong communication and stakeholder management More ❯
the risk models and working closely with underwriting and technical modelling teams. ✔️ Personal Lines Pricing experience (Motor, Home or Pet) ✔️ Strong skills in predictive modelling – e.g., GLMs, GBMs, GAMs, Random Forests ✔️ Proficiency in R, Python, PySpark, SAS or SQL ✔️ Experience with Radar and/or Emblem ✔️ A numerate degree (e.g., Maths, Stats, Actuarial, Engineering) ✔️ Strong communication and stakeholder management More ❯
of mathematical competence. The ability to code or have programming experience, especially in Python. Some experience with theoretical concepts of statistical learning (e.g. hypothesis testing, Bayesian Inference, Regression, SVM, Random Forests, Neural Networks, Natural Language Processing, optimisation). Experience with some coding libraries frequently used in data science. The ability to communicate effectively. Experience composing and following a project More ❯
