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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Scientist Enterprise Data Intelligence - **Company:** Houston Independent School District - **Location:** Houston, TX, United States - **Experience:** Expert - **Salary:** $92,540.0 - $152,691.0 - **Contract:** Permanent contract - **Skills:** Data Governance, Data Presentation, Data Structures, Decision Support Systems, R (Programming Language), Data Intelligence, Python (Programming Language), Machine Learning, Power BI, SQL Databases, Enterprise Data Management, Microsoft Fabric - **Published:** May 23, 2026 - **Apply:** https://www.careerjet.com/jobad/usb03b48a5e9953133c0c22f9e8ec9ae6e ## About the Role 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. ## WORK EXPERIENCE Minimum of 6 years in data science, research, or applied analytics roles. Experience in public education, government, or nonprofit analytics preferred. ## SKILL AND/OR REQUIRED LICENSING/CERTIFICATION * 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. ## WORK COMPLEXITY/INDEPENDENT JUDGMENT Manages high-impact modeling projects with districtwide consequences. Applies independent professional judgment to determine methods and interpret results. ## BUDGET AUTHORITY None. May advise on data tools, modeling platforms, and external datasets. ## PROBLEM SOLVING Translates strategic questions into analytical models. Identifies data issues and proposes data-informed solutions. ## IMPACT OF DECISIONS Models influence district investment decisions, student support strategies, and strategic planning efforts. ## COMMUNICATION/INTERACTIONS Collaborates with department leads, executive staff, and board advisors. Presents findings to senior leadership and external partners. ## CUSTOMER RELATIONSHIPS Provides critical insight and foresight to HISD leadership teams. Builds stakeholder trust through actionable, validated analytics. ## WORKING/ENVIRONMENTAL CONDITIONS Office environment. May work extended hours during major board cycles or forecasting updates. Houston Independent School District is an equal opportunity employer. ## Description 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. ## MAJOR DUTIES & RESPONSIBILITIES 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. ## MAJOR DUTIES & RESPONSIBILITIES CONTINUED 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\. 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