Data Scientist Intermediate.

ResponsibilitiesProvides mentoring and guidance to other, more junior Data Scientists and staffSupport the development of internal web applications or interactive tools that help operationalize and deliver data science products across the organization.Acts as mentor and DS SME for other more junior DS users across the state and key external stakeholdersEngages with key business stakeholders on large projects and initiatives to understand their analytical and operational challenges and translate these needs into data solutionsAssesses the structure, content, and quality of the data through examination of source systems and data samplesCollaborates with other DS professionals, data engineers, and BI professionals around data/table structures to optimize architecture, ETL procedures, dashboards, and other self-service needsPrioritizes requirements and create rapid prototypes and minimally viable products for end usersLooks for opportunities to improve current processes or find efficiencies by applying industry best practices as a DS professionalMines and analyzes data from state databases to drive insights into problems and efficiency in processes while maintaining the standards of organizational excellenceInterprets data and from multiple sources using a variety of analytical techniques, ranging from simple data aggregation, to data mining, to more complex statistical methodologiesUses and monitors the input for code repositories like GitHub for code version controlProvides end user education for interpretation of business dataTests and evaluates data solutions as it relates to upgrades to existing softwareProvides maintenance and support for existing data solutions for the agencyDocuments and communicates technical specifications to ensure that proper techniques and standards are incorporated into deliverables and understood by the end usersRequired QualificationsBachelor's Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics and 2+ years of experienceOr a Master's Degree with course work in analytics, statistics, computer science, informatics, and/or mathematics4+ years of experience and passion for leveraging data to drive significant organizational impactConsiderable knowledge using computer languages (R, Python, SQL, etc.) to manipulate and draw insights from large data sets as well develop software for automationBroad knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applicationsBroad knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages and drawbacksStrong understanding of relational and dimensional databases, theories, principles, and practicesExceptional analytical, conceptual, and problem-solving abilitiesMust inhabit strategic thinkingStrong written/oral communication and presentation skillsResourceful self-starter and highly motivated team playerAble to perform well in a fast-paced environmentPreferred QualificationsExperience with data manipulation to include cleansing, standardizing, and transformingExperience in leading workshops or training sessions with a user community a plusExperience generating and distributing visualizations to a broad range of audiencesProficiency using frameworks such as Shiny, Dash, Flask, or Streamlit to build user-facing interfaces, connect to backend data pipelines, and deploy lightweight analytic applicationsExperience with the following concepts or tools (geocoding and geospatial data, shiny, network diagraming, neo4j, Docker, Kubernetes)