Description

The Virginia Office of Data Governance and Analytics is an exciting new agency under the Secretary of Administration. The agency’s primary focus is Data Sharing and Data Governance. The agency manages the Commonwealth Data Trust to facilitate data sharing across the Commonwealth and its partners; and provides administrative support to the Commonwealth Data Commission, Executive Data Board, Data Governance Council, and Data Stewards Group. In addition, the Office of Data Governance and Analytics (ODGA) will provide guidance, support, oversight, and technical assistance to data trust member agencies and Commonwealth organizations in the implementation of data governance, sharing, security, and analytics projects.

Responsibilities:

• Understand and translate business needs into data models supporting long-term ODGA solutions.

• Develop and maintain conceptual, logical and physical data models along with corresponding metadata.

• Develop best practices for data standards and coding practices to ensure consistency in data models.

• Perform reverse engineering of physical data models from databases and SQL scripts.

• Examine new application design and recommend corrections if required.

• Develop tools for data science staff that enable them to derive actionable insights into business operations and performance measures from data sets.

• Develop successful prototypes and proofs of concept to improve system components and tools and to demonstrate new functions.

• Advise technical staff on data flow, processing issues, and other topics pertinent to the generation of data that meets business requirements.

• Collaborate effectively with partner agencies and business stakeholders in order to address data-related technical issues, clarify business requirements, and resolve conflicts and ambiguities. 

• Serve as a data scientist resource to data trust member agencies and Commonwealth organizations regarding machine learning issues. 

• Support data quality, integrity, security services in partner agencies as a core value.

Competencies Required:

• Considerable experience using statistical computer languages (R, Python, etc.)

• Considerable experience working with and creating data architectures.

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

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

• Excellent written and verbal communication skills for coordinating across teams.

• A drive to learn and master new technologies and techniques.

Qualifications:

• Bachelor’s degree plus 5 years of Data Science experience.

• Practical programming experience in Python, R, Spark, SQL, and/or other data scripting languages (3 years preferred).

• At least 3 years of experience in Python, R, and/or other data scripting languages.

• At least 3 years of experience utilizing a business intelligence visualization tool (Power BI, Tableau, etc.).

• At least 3 years of experience in querying and analyzing and working with data languages and platforms (SQL) to investigate large and diverse data sets.

Requirements

Considerable experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Required 5 Years

Considerable experience working with and creating data architectures. Required 5 Years

Considerable knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.). Required 5 Years

Considerable knowledge of relational databases such as SQL Server. Required 5 Years