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.Responsibilities:
- Be the go-to-person for data pipelines to support operational implementation of Data Science and analytical models.
- Engineer each solution with serverless technology when possible, with optimized performance.
- Execute analytics solution engineering strategy, requirements, and adapt processes as needed.
- Perform DevOps and orchestration around supporting data marts and analytical processes.
- Monitor and secure usage of data while tracking analytic product performance.
- Advise and collaborate in internal partnerships to deliver accurate, available, and accessible API services.
- Ensure all security, documentation, governance, and compliance standards are met.
- Manage small reporting layer on top of analytical models to ensure accountability and insight into models’ performance and impact.
- Identifies potential concerns based on projections of current trends.
- Experience developing business analytical solutions in large or midsize companies.
- Must be able to manage multiple tasks simultaneously and react to problems quickly.
- Contribute to Credit Union culture by keeping a positive attitude and growing relationships
- Understanding of the financial services industry desired.
- Experience with dashboard design and delivery desired
- Must be able to translate concepts and directions into practical solutions.
- Must have development experience with various data management technology; NoSQL; relational database; message broker; multi-dimensional database; and design architecture.
- Understand data collection, streaming, preparation, analysis, visualization, modeling, algorithm integration, evaluation, optimization within an implementation context.
- Must have advanced SQL abilities, experience with both Oracle and Microsoft desired.
- Must have advanced programming experience with Python
- Must have experience with Linux.
- Experience with Anaconda; RabitMQ; Jupyter Notebook; Tableau desired
- 3+ years of experience in designing, developing and implementing Data Science solutions.
- Bachelor of Science degree in information technology, computer science, statistics, or related business degree with equivalent experience of 3 years.
- Master of Science in information technology, computer science, statistics, or related degree.