Data Scientist Intermediate.

Responsibilities

• Provides mentoring and guidance to other, more junior Data Scientists and staff

• Support 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 stakeholders

• Engages with key business stakeholders on large projects and initiatives to understand their analytical and operational challenges and translate these needs into data solutions

• Assesses the structure, content, and quality of the data through examination of source systems and data samples

• Collaborates with other DS professionals, data engineers, and BI professionals around data/table structures to optimize architecture, ETL procedures, dashboards, and other self-service needs

• Prioritizes requirements and create rapid prototypes and minimally viable products for end users

• Looks for opportunities to improve current processes or find efficiencies by applying industry best practices as a DS professional

• Mines and analyzes data from state databases to drive insights into problems and efficiency in processes while maintaining the standards of organizational excellence

• Interprets data and from multiple sources using a variety of analytical techniques, ranging from simple data aggregation, to data mining, to more complex statistical methodologies

• Uses and monitors the input for code repositories like GitHub for code version control

• Provides end user education for interpretation of business data

• Tests and evaluates data solutions as it relates to upgrades to existing software

• Provides maintenance and support for existing data solutions for the agency

• Documents and communicates technical specifications to ensure that proper techniques and standards are incorporated into deliverables and understood by the end users

• Required Qualifications

• 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

• 4+ years of experience and passion for leveraging data to drive significant organizational impact

• Considerable knowledge using computer languages (R, Python, SQL, etc.) to manipulate and draw insights from large data sets as well develop software for automation

• Broad knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

• Broad knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages and drawbacks

• Strong understanding of relational and dimensional databases, theories, principles, and practices

• Exceptional analytical, conceptual, and problem-solving abilities

• 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

Preferred Qualifications

• Experience with data manipulation to include cleansing, standardizing, and transforming

• Experience in leading workshops or training sessions with a user community a plus

• Experience generating and distributing visualizations to a broad range of audiences

• Proficiency using frameworks such as Shiny, Dash, Flask, or Streamlit to build user-facing interfaces, connect to backend data pipelines, and deploy lightweight analytic applications

• Experience with the following concepts or tools (geocoding and geospatial data, shiny, network diagraming, neo4j, Docker, Kubernetes)