Houston Independent School District

Architect Performance Management Data Science

Education, Government & Non-Profit
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data science or related field
  • Advanced degree in statistics, computer science, or a related discipline
  • Expertise in statistical modeling and machine learning techniques
  • Strong skills in data engineering and pipeline construction
  • Proficiency in analyzing large-scale datasets with educational applications
  • Ability to communicate complex analytical results to non-technical stakeholders

Responsibilities

  • Design and implement end-to-end data pipelines
  • Apply statistical and machine learning techniques to derive insights
  • Analyze district-wide educational datasets for strategic decision-making
  • Translate complex analysis into actionable insights for leadership
  • Utilize independent judgment to select analytical methodologies for unique challenges

Benefits

  • Professional development opportunities
  • Access to advanced technology and tools
  • Collaborative work environment
  • Flexible work schedules to support work-life balance
Full Job Description
The Performance Management Data Science Architect has specialized training in statistical modeling, data engineering, and computational analysis to support district-wide strategic decision-making. This role requires the application of advanced theoretical and practical knowledge in data science, statistics, and computer science to analyze large-scale educational datasets, develop predictive models, and design data-driven solutions that improve student outcomes and operational performance. The Data Science Architect is responsible for designing and implementing data pipelines, applying statistical and machine learning methodologies, and translating complex analytical results into actionable insights for executive leadership. The role requires independent judgment in selecting appropriate analytical techniques and tools to address non-routine, complex problems.

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