Location: Hattie Mae White
Department: Enterprise Systems Data Intelligence
Area:District Wide
Contract Months:12
Salary Range: $92,540.00 – $152,691.00
Academic Year: 26-27
The Sr. Data Scientist Enterprise Data Intelligence leads advanced analytics initiatives that inform strategic planning, equity initiatives, forecasting, and resource allocation across both instructional and operational domains. This role builds predictive models, simulations, and complex analyses using data from student systems (SIS, LMS, SPED) and enterprise systems (finance, HR, procurement). The Senior Data Scientist works closely with senior leaders and analysts to deliver evidence-based insights that shape district policies and performance outcomes.
List most important duties first
1. Design and implement predictive models and machine learning algorithms for student outcomes, budgeting, staffing, and resource planning.
2. Analyze districtwide data to support equity tracking, chronic absenteeism, enrollment forecasting, and SPED identification trends.
3. Integrate data from Microsoft Fabric, SIS, ERP, and external datasets to answer complex research questions.
4. Develop simulations and decision support tools to guide executive and board-level planning.
5 Present findings using compelling visuals and narratives tailored to non-technical audiences.
6. Partner with academics, operations, and finance to align data insights with real-world decisions.
7. Maintain reproducible research workflows and ensure compliance with data governance policies.
8. Collaborate with data architects and engineers to ensure model-ready datasets are accurate and current.
9. Mentor analysts and support the expansion of data fluency across departments.
10. Perform other job-related duties as assigned.
A Master's degree in data science, statistics, applied mathematics, economics, or a related field is preferred. Alternatively, a Bachelor's degree plus relevant work experience is acceptable.
Applicants who do not meet these education qualifications may be considered if they have a unique combination of education and work experiences that indicate potential for success in this role.
Minimum of 6 years in data science, research, or applied analytics roles. Experience in public education, government, or nonprofit analytics preferred.
• Expert proficiency in Python, R, SQL, and Power BI
• Strong statistical and machine learning skills (e.g., regression, classification, time series, clustering)
• Familiarity with education data structures and public sector decision-making
• Data storytelling and visualization expertise
Serves as senior technical leader within the Data Intelligence Office. May lead projects and mentor junior analysts.
Manages high-impact modeling projects with districtwide consequences. Applies independent professional judgment to determine methods and interpret results.
None. May advise on data tools, modeling platforms, and external datasets.
Translates strategic questions into analytical models. Identifies data issues and proposes data-informed solutions.
Models influence district investment decisions, student support strategies, and strategic planning efforts.
Collaborates with department leads, executive staff, and board advisors. Presents findings to senior leadership and external partners.
Provides critical insight and foresight to HISD leadership teams. Builds stakeholder trust through actionable, validated analytics.
Office environment. May work extended hours during major board cycles or forecasting updates.
Houston Independent School District is an equal opportunity employer.
The Houston Independent School District is the largest public school system in Texas and the eighth largest in the United States. Its schools are dedicated to giving every student the best possible education through an intensive core curriculum and specialized, challenging instructional and career programs. HISD is empowers students to become critical thinkers, visionary leaders, and active contributors in their community, fostering a pathway to success for limitless opportunities in a competitive global landscape.
