Qualifications Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., LogisticRegression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT More ❯
probability theory, or optimization. Experience and training in finance and operations domains. Deep experience with ML approaches: deep learning, generative AI, large language models, logisticregression, gradient descent. Experience wrangling complex and diverse data to solve real-world problems. What's it like to work here: You will More ❯
and Docker is a positive. An understanding of machine learning processes and their applications to investments. Ideally, they will be familiar with various algorithms (logisticregression, neural networks) and an understanding of how to implement these in Python. A passion for bringing together investment ideas in an organized More ❯
Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. 5+ years of data scientist experience. Experience with statistical models e.g. multinomial logistic regression. PREFERRED QUALIFICATIONS Experience working with data engineers and business intelligence engineers collaboratively. Experience managing data pipelines. Experience as a leader and mentor on More ❯
the main concepts of Data Science/Machine Learning would be useful. We use a range of predictive analytics and machine learning methodologies, including logisticregression and cluster analysis, plus some predictive time series analysis. More ❯
the main concepts of Data Science/Machine Learning would be useful. We use a range of predictive analytics and machine learning methodologies, including logisticregression and cluster analysis, plus some predictive time series analysis. More ❯
Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. 5+ years of data scientist experience. Experience with statistical models e.g. multinomial logistic regression. Experience developing neural network models. PREFERRED QUALIFICATIONS 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience. Experience managing data More ❯