Data Scientist

Overview

Under general supervision, the position leads the development and application of methods to identify, collect, process, organize, and analyze structured, semi-structured, and unstructured data using advanced statistical prediction, inference, and optimization; effectively communicates results and provides ongoing support to strengthen data-driven program design and management. This position will play a critical role in transforming court operational data into actionable insights that support judicial leadership, circuit management, and statewide reporting consistency.

The Data Scientist will collaborate with IT leadership, court administrators, clerks, judges, and executive stakeholders to develop predictive models, performance dashboards, and analytical frameworks that improve transparency, efficiency, and data-driven decision-making across the Judicial Branch.

• Judicial Performance Analytics. Independently conduct advanced analytical studies for the resolution of business problems and transfigures data into critical information by selecting and deploying appropriate advanced statistical techniques such as machine learning, bivariate and multivariate analyses, predictive/prescriptive analytics, and optimization. Develop statistical model to evaluate: case aging trends, disposition rates, backlog indicators, and circuit/county level performance disparities. Design benchmarking methodologies. Conduct time-series analysis across fiscal years.
  
  Identity patterns in filings, dispositions, and case durations. Provide advanced metrics beyond standard reporting counts.
• Dashboard & Executive Reporting Enhancement. Design and optimize dashboards, visualizations, and analytic tools (e.g., Periscope, Business Objects, D3, ggplot, etc.). Develop advance DAX-backed measures ground in statistical rigor. Parner with Power BI developers to enhance dashboards. Translate complex findings into executive-ready visualization. Support development of KPI frameworks for statewide reporting. Convey findings and conclusions of work orally, in writing, visually, in presentations, and by developing interactive tools as appropriate to communicate effectively with a wide range of audiences, including technical and nontechnical staff, stakeholders, and executive leadership.
• Data Quality & Governance Support. Identify data inconsistencies across statewide data. Develop anomaly detection routines. Collaborate on improving the data collection into the statewide data warehouse. Support data standardization effort. Assist with validation logic for DW ETL processes. Provide ongoing tracking and monitoring of performance of decision systems and statistical models and troubleshoots and implements enhancements and fixes to systems as needed.
• Predictive & Advanced Modeling. Build predictive models for judicial data. Create and maintain a LLM with judicial data for effective searching and reporting. Develop risk indicators for emerging congestion. Apply regression, clustering, and classification techniques for judicial datasets. Use statistical computer scripting, domain-specific, and programming languages and other software and tools to digest, manipulate, prepare, augment, evaluate, analyze, summarize, and visualize data.
• Research & Policy Support. Conduct statistical analysis to support:
  1) Legislative inquiries
  2) Policy reviews and
  3) 610 data requests. Stays current with best practices; access ongoing training and professional development to maintain familiarity with current industry research to apply the latest and most useful statistical learning techniques to help extract pattern and trends from data. Assist in implementing recommended process changes in ways that both retain fidelity to best practices identified through the analysis and recognize the operational realities underlying existing business processes, provides ongoing consultation as recommended changes and new programs grow and evolve, including recommending modifications to adopted goals and metrics.
• Collaboration and Stakeholder Engagement. Collaborate with other department subject matter experts to understand, identify, and select available and relevant sources of data for use cases, including internal, external, structured, semi-structured, and unstructured data sources; and provides guidance to other department data experts in the selection and transformation of such sources
• Performs all other duties as assigned.

Qualifications include:
Masters in Data Science, Applied Mathematics, Statistics, Information Technology, Computer Science, Economics or another quantitative field;
Seven (7) years of experience applying machine learning, predictive analytics, data management, and hypothesis-driven data analysis to produce actionable recommendations to support data-driven program, policy, and operational decision-making;
Advanced proficiency in R and/or Python for data analysis and modeling;
Experience with SQL and relational…