Responsibility:
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Build and enhance Non-SQL/SQL based data analytics processes through all phases of development, implementation, and upkeep.
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Unlock insights by analyzing large scale of complex numerical and textual data and identifying trends.
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Create and maintain reporting dashboards to deliver data insights to a wide range of consumers.
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Partner with a cross-functional team of data engineers, machine learning engineers, and data visualizers to deliver projects.
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Develop data science solutions utilizing both on-premises and Microsoft Azure Cloud Computing Infrastructures.
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Perform other duties as assigned.
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Qualifications:
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Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field (or equivalent work experience).
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Experience with cloud computing infrastructure.
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Minimum of 5 years of experience in Data Analysis, SQL/Python Programming, and Plotly Enterprise or Power BI development.
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Strong understanding of database design, data mining, and data modeling concepts.
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Experience with ETL processes and data integration techniques.
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Proven ability to develop effective data visualizations using Power BI and/or Plotly Enterprise.
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Advanced verbal, written, interpersonal, and presentation skills to communicate clearly and concisely technical and non-technical information to all levels of management.
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Desired:
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Advanced degree in in computer science, mathematics, physics, statistics, or related field.
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Advanced skills with Python, Jupyter Notebook/Jupyter Lab, Visual Studio Code and other languages/frameworks appropriate for large data analysis.
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Experience with supervised/unsupervised machine learning model development in areas of clustering, classification and/or regression.
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Experience with No-SQL databases such as MongoDB and Cassandra
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Experience with API end point connection and configuration for complex data pipelines.
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Experience establishing data governance principals as part of the data ingestion process.
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Experience working with Agile principals utilizing Azure DevOps or similar systems.
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Experience working in the Financial Industry
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