ENTERPRISE DATA SCIENTIST - 77777

The Data Scientist will serve as a technical and analytical leader responsible for advancing the States use of process mining, process intelligence, and data-driven operational improvement through Celonis. This position will work with business, technical, and executive stakeholders to identify high-value process improvement opportunities, integrate and transform enterprise data, develop analytical models, and deliver actionable insights that improve efficiency, compliance, service delivery, and decision-making. This role requires strong technical expertise in data analysis, data modeling, process mining, business intelligence, and enterprise systems. The position will help lead the design, implementation, governance, and expansion of Celonis solutions across supported business areas, including ERP and agency processes. The ideal candidate will be able to bridge the gap between business operations, enterprise data, technology teams, and executive leadership. He/She has strong experience, 1. Lead the design, development, implementation, and ongoing enhancement of Celonis process mining and process intelligence solutions for high-value enterprise and agency business processes.

1. Partner with agency stakeholders, STS teams, business process owners, technical teams, and vendor partners to identify process improvement opportunities, define success measures, and deliver actionable insights.
2. Analyze complex operational, transactional, ERP, and process event data to identify bottlenecks, rework, compliance deviations, cycle time issues, automation opportunities, and measurable business value.
3. Develop and maintain data models, analyses, dashboards, KPIs, action flows, process views, and value tracking capabilities that support executive and operational decision-making.
4. Lead or support data extraction, transformation, validation, and integration from Edison, agency systems, databases, data warehouses, APIs, and other enterprise sources into Celonis and related analytics platforms.
5. Translate business rules, process requirements, and operational objectives into analytical solutions, documented metrics, data definitions, transformation logic, and recommended actions.
6. Provide technical leadership, guidance, documentation, and knowledge transfer to analysts, developers, and business users while ensuring appropriate data governance, security, privacy, and quality practices.

with SQL, data analysis, business intelligence, enterprise systems, and process improvement, with preferred experience in Celonis, ERP analytics, Python, and public sector technology environments., 1. Bachelor’s Degree in computer science, information technology or data management. Relevant professional technology experience may be substituted for the required degree

1. Experience working with large, complex datasets from enterprise systems, transactional systems, data warehouses, or operational applications.

2. Experience using SQL for data extraction, transformation, validation, and analysis.

3. Experience with programming or scripting languages, such as Python, R, or JavaScript, to support data analysis, automation, data transformation, statistical modeling, and analytical solution development.

4. Experience developing dashboards, analytical models, reports, or visualizations that communicate business insights.

5. Experience translating business requirements, process rules, and operational needs into analytical solutions.

6. Strong understanding of data quality, data governance, data privacy, and data lifecycle management.

7. Ability to communicate effectively with executive, business, and technical audiences.

8. Ability to work collaboratively across teams and influence stakeholders toward consensus and measurable outcomes.

Preferred Qualifications:

1. Masters degree in data science, analytics, computer science, statistics, mathematics, information systems, or a related field

2. Experience with Celonis, process mining, process intelligence, business process analytics, or process improvement platforms.

3. Experience with ERP business processes

4. Experience with business intelligence and visualization tools such as Tableau, Power BI, Oracle Analytics Cloud, Oracle DV, or similar platforms.

5. Experience with ETL or data integration tools such as ODI, Informatica, cloud-based data pipelines, APIs, or SQL-based transformation frameworks.

6. Experience with designing process KPIs, operational metrics, value tracking models, or executive-level performance dashboards.

7. Experience with machine learning, predictive modeling, anomaly detection, or AI-enabled analytics. 8. Experience working in state government, public sector, shared services, ERP support, or enterprise IT environments.