
Senior Data Scientist
at world’s first real-time opportunity engine. We constantly cr


● Statistics - Always makes data-driven decisions using tools from statistics, such as: populations and
sampling, normal distribution and central limit theorem, mean, median, mode, variance, standard
deviation, covariance, correlation, p-value, expected value, conditional probability and Bayes's theorem
● Machine Learning
○ Solid grasp of attention mechanism, transformers, convolutions, optimisers, loss functions,
LSTMs, forget gates, activation functions.
○ Can implement all of these from scratch in pytorch, tensorflow or numpy.
○ Comfortable defining own model architectures, custom layers and loss functions.
● Modelling
○ Comfortable with using all the major ML frameworks (pytorch, tensorflow, sklearn, etc) and NLP
models (not essential). Able to pick the right library and framework for the job.
○ Capable of turning research and papers into operational execution and functionality delivery.

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