Roles bull Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements, specification, processing, analysis, ongoing deliverables, and presentations. bull Build and prototype analysis pipelines iteratively to provide insights at scale. bull Deliver a Machine Learning (ML) project from beginning to end, including understanding the business need, aggregating data, exploring data, building validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organization bull Develop custom data models and algorithms to apply to data sets. bull Use Public Cloud Artificial Intelligence (AI) services (e.g., Personalize), ML platforms, and frameworks (e.g., MXNet, TensorFlow, PyTorch, SparkML, scikit-learn) bull Research and implement novel ML approaches, including hardware optimizations on platforms. bull Leverage company data to drive business solutions for enterprise clients using R, Python or other tools. bull Analyze, extract, normalize, and label relevant data, to operationalize machine learning models after they are prototyped bull Assess Model accuracy using common metrics (AUC, F1, etc.) and explain the results to the stakeholders. Required Qualifications bull Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory. bull 4+ years of industry experience in predictive modeling, data science, and analysis. bull Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models bull Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility. bull Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models. bull Bachelorrsquos degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience. Preferred Qualifications bull Masterrsquos degree of PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.). bull Ability to develop strategic, baselined, data modeling processes ability to accurately determine cause-and-effect relationships. bull Publications or presentations in recognized ML journals or conferences. bull Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within our organization. bull Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.