Skills | Years Used | Last Used | Competence Level |
Bachelor s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics and 2+ years of experience Or a Master s Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics or 4+ years of experience and passion for leveraging data to drive significant organizational impact. | | | |
Exp w/Shiny, Dash, Flask,or Streamlit to build user-facing interfaces, connect to backend data pipelines, and deploy lightweight analytic applications | | | |
Experience connecting to backend data pipelines, and deploy lightweight analytic applications | | | |
Experience using (R, Python, SQL, etc.) to manipulate and draw insights from large data sets as well develop software for automation | | | |
Advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) | | | |
Experience with data manipulation to include cleansing, standardizing, and transforming | | | |
Broad knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) | | | |
Strong understanding of relational and dimensional databases, theories, principles, and practices | | | |
Experience in leading workshops or training sessions with a user community a plus | | | |
Exceptional analytical, conceptual, and problem-solving abilities | | | |
Experience generating and distributing visualizations to a broad range of audiences | | | |
Must inhabit strategic thinking | | | |
Strong written/oral communication and presentation skills | | | |
Resourceful self-starter and highly motivated team player | | | |
Able to perform well in a fast-paced environment | | | |
Effective communicator and someone who enjoys getting to understand nuances of a problem | | | |
Experience with the following concepts or tools (geocoding and geospatial data, shiny, network diagraming, neo4j, Docker, Kubernetes) (Highly Desired) | | | |