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