Data Scientist

The Data Scientist plays a key role by creating in-depth analyses by leveraging data science techniques, methods, and interpretations to convey accurate, meaningful insights that empower IDOH and other partners to make informed decisions in support of the health, safety, and well‑being of the citizens of Indiana.

• Provides mentoring and guidance to other, more junior Data Scientists and staff
• Supports 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 creates 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 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 Git Hub 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 end users

The job profile is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Other duties, responsibilities and activities may change or be assigned at any time with or without notice.

• The ideal candidate in this role should minimally have either:
  • A Bachelor’s Degree with coursework in analytics, statistics, computer science, informatics, and/or mathematics and 2+ years of experience and passion for leveraging data to drive significant organizational impact
  • or a Master’s Degree with coursework in analytics, statistics, computer science, informatics, and/or mathematics
  • or 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 as 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
• Experience with data manipulation to include cleansing, standardizing, and transforming
• Experience in leading workshops or training sessions with a user community a plus
• Experience with the following concepts or tools is not a requirement but considered a plus (geocoding and geospatial data, shiny, network diagramming, neo4j,…