rate for the right candidate. Hybrid working model - 3 days in office Highly experienced in Python and SQL - as well as time series & bayesian modelling. Background in STEM Financial Services experience needed This role is urgently required so the clients will need candidates to start ASAP. Ready more »
Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge in operational and support functions of Banking and/or Insurance as well as associated modeling and analytics more »
Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge in operational and support functions of Banking and/or Insurance as well as associated modeling and analytics more »
Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge in operational and support functions of Banking and/or Insurance as well as associated modeling and analytics more »
Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators. Strong business context knowledge in operational and support functions of Banking and/or Insurance as well as associated modeling and analytics more »
years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java) 4+ years of experience with Bayesianstatistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or timeseries analysis required Basic Qualifications: Must be able to think conceptually, strategically more »
at least three of the following areas: Generative AI, Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Recommendation Systems, Knowledge Graphs, Probabilistic Inference, BayesianStatistics, Reinforcement Learning. Strong industry experience, with a focus on taking concepts and models from conception to production and quantifying business impact. Proficiency more »
a client-friendly manner. Experience: Experience in a similar role within a Media Agency environment, delivering MMM and attribution model projects. Proficiency in Bayesianand linear regression approaches; familiarity with other machine learning techniques is advantageous. Extensive experience in data mining and analysis, including designing methodologies to more »
process monitoring Developing soft sensors based on PLS and neural net models to predict slurry particle size and viscosity Implementing Bayesianmethodsand/or state-of-the-art methods for optimising the Design of Experiments approach. Working with clients to increase their sustainability footprint more »
knowledge in a dynamic work environment. Desirable Experience: Hands-on experience with computational models that simulate cellular disruptions. Knowledge of Bayesianmethodsand proactive machine learning techniques. Practical experience in developing AI-driven generative models, particularly those involving transformer architectures. A demonstrated passion for research into more »
