experience as a data scientist; manipulating data sets and building statistical models, knowledge of a variety of machine learning techniques (clustering, decisiontree learning etc.) and their real-world advantages/drawbacks. Experience working with audio and video data formats and familiarity with deep learning techniques. While more »
manipulation and analysis libraries (e.g., pandas, numpy, jupyter, scikit-learn). Knowledge of machine learning and statistical methods (e.g. linear/logistic regression, decisiontrees, random forest, unsupervised methods) is preferred. Ability to convey complex information through data visualisation. Ability to manage different responsibilities and adapt to changing more »
ethical use of AI, ensuring compliance with internal policies and external regulations. Deep understanding of traditional AI techniques: regression, classification, forecasting, clustering (e.g., DecisionTrees, XGBoost, ARIMA, etc.) Strong understanding of programmatic LLM risk controls: output format validation, output context validation, content moderation etc. There is a lot more »
driven business transformation journey Develop tools for monitoring and analysing model performance and data precision. Present model findings and offer recommendations to key decision-makers and stakeholders The candidate: MSc/PhD in Data Science, Computer Science, Financial Engineering, Statistics, or related fields. 5+ years of industry experience … including distributions, statistical testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decisiontrees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior more »