Key Skills Required Professional Skills • Machine learning forecasting techniques Fully Operational. • Statistical modelling Fully Operational. • Operational research and supply chain Working Knowledge. • Optimization techniques and tools Fully Operational. • Manipulating multi-source data Fully Operational. • Python coding Fully Operational. • Cloud architecture (preferably MS Azure) Working Knowledge. • Simulation packages e.g. Any logic Working Knowledge. • Distributed computing (Hadoop, Spark) Working Knowledge. General Skills • Project Management Working Knowledge. • Communication / presentation skills Working Knowledge. Strong communication skills and ability to work with peers and demonstrate vertical and lateral influence. Limitless curiosity and imagination to create novel business solutions. Relevant Experience • B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Engineering, or Mathematics). • 1-4+ years’ work experience in a data science role with significant focus on large scale and/or unstructured data. • Experience managing projects from start to finish. • Passion for empirical research and for answering hard questions with data. • Ability to apply an agile analytic approach that allows for results at varying levels of precision. • Ability to communicate complex quantitative insights in a precise, and actionable manner to business leaders. • Strong track record in solving analytical problems using quantitative and machine learning approaches o Working knowledge in common machine learning techniques such as Random Forests, Boosting, Regularized Regression, Naïve Bayes Classifiers. • Working knowledge of advanced machine learning such as Deep Neural Networks, Support vector machines, Reinforcement learning and Bayesian networks. • Working knowledge in classical statistics (Regression, Clustering, Optimization, Time Series, Probability). • Deep experience in testing and measurement (A/B, multivariate, inferential measurement e.g. Causal Impact). • Deep experience working with and coding in R, R Shiny, Python. • Working knowledge of data visualization concepts in reports (Power BI) and specialist tools (D3 or equivalent) • Working knowledge working with large data sets, experience working with distributed computing tools a plus (Apache Spark, Hive, Impala) • Working knowledge working in Microsoft Azure and scaling analytic products over GPUs in the cloud • Knowledge of extracting and combining complex, high-volume, high-dimensionality data from multiple sources (enterprise, proprietary, IoT, public domain), including unstructured data (comment threads, audio, video)