This position is responsible for aiding operational areas of the organization leveraging both internal and external data assets to achieve business insights, gain deeper understanding of member needs, and enhance tactical and strategic decision making.
NATURE AND SCOPE:
Collaborates with data science team to extract analytical, behavioral and predictive data sets and data pipelines from ever increasing data resources. Understands progressive statistical, programmatic, and analytical approaches to business hypotheses as it applies to available data. Aids business owners & data science team in the interpretation of source data and associated business data pipelines. Requires a solid understanding of both the technical and business aspects of Data Science and business analytics. Requires full software development life cycle experience within various analytical architectures, including piloting models, architecting underlying data design, and model operationalization. Models will be deployed using agile methodologies to ensure timely and relevant delivery.
Responsible for the design, development, and maintenance of analytical models that will be placed into operation. Will be required to explore internal and external data sources to identify useful structures within the data that were/are previously unknown to the business. Should have a strong understanding of relational and dimensional modeling to facilitate data wrangling, model operationalization, and exploration of data. Responsible for adhering to corporate data governance policy and controls to ensure the accuracy, timeliness and confidentiality of resources under management. Must be able to work with users from all levels of management in developing and implement operational and strategic analytics. The Machine Learning Engineer’s primary focus will be on operationalization of analytical models.