Job description

We are seeking a Mid-level to Senior Data Science Consultant to support data cleanup, analytics, and governance initiatives for vertical asset data. The consultant will play a key role in ensuring data accuracy, consistency, and quality by leveraging analytics, automation, and visualization tools. This position requires a blend of technical proficiency, analytical thinking, and strong communication skills to collaborate with cross-functional teams and data owners. Key Responsibilities ] • Utilize advanced analytics techniques to automate the correction of asset attribute data for records already in the database. • Develop and execute queries and scripts to identify and replace incorrect or missing data attributes based on asset Type, Class, and related fields. • Produce, test, and run code to query specific fields or character strings and apply data corrections efficiently. • Design and implement a Power BI dashboard to highlight data quality issues and enable Asset System Managers (ASMs) to monitor and prioritize improvements. • Contribute to the development and review of data governance processes and data standards for vertical assets. • Conduct comprehensive analysis of data integrity within the TEAMS system and document findings through clear reports, visuals, and memos. • Collaborate with data owners to verify, correct, and enhance data accuracy. • Identify and recommend process improvement opportunities based on data-driven insights. • Develop tools and scripts in SAS or other approved software (Python, Azure tools, etc.) for continuous data quality monitoring. • Provide documentation, process maps, and training to WSSC staff to ensure sustainability of data governance practices. Required Skills & Experience • 5- 10 years of experience in Data Science, Data Engineering, or Data Analytics roles. • Proficiency in: • SQL (complex queries, data manipulation, and optimization) • Power BI (dashboard creation, DAX, and data modeling) • Python or other scripting languages (for automation and data processing) • Azure Data Services (Data Factory, Synapse, or related tools) • Experience working with multiple data sources, including structured and unstructured data. • Strong understanding of data governance principles, metadata management, and data quality frameworks. • Excellent analytical, documentation, and communication skills to present findings to both technical and non-technical audiences. Preferred Qualifications • Experience working with utility or public sector asset management systems (e.g., TEAMS). • Knowledge of data standards and governance frameworks for asset-intensive organizations. • Hands-on experience with data quality and cleansing automation techniques.

Requirements