Director, Research
Listed on 2026-08-16
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Research/Development
Research Analyst, Data Scientist
Director Of Research
The Director of Research ensures that Commit uses the best available empirical evidence to inform decisions internally and with external partners. Working within Commit's priority areas, the Director shapes and executes a research and evaluation agenda that serves the organization's Dallas County and statewide goals, determining what works, for whom, and under what conditions, and translating findings into credible recommendations that district leaders, funders, board members, and policymakers can act on.
Reporting to the Managing Director of Research, Analytics, and Data, the Director leads a research team and serves as the organization's authority on methodological rigor, ensuring that the evidence behind Commit's programmatic and policy work holds up to scrutiny.
This position also looks ahead to identify the priorities that can work mit's place in the education ecosystem gives the Director a hand in shaping how students learn, how teachers are trained, and how outcomes improve statewide. It suits someone who thinks at the systems level and understands how actionable research, communicated clearly and to the right people, can support students across Texas.
The role requires a researcher with deep methodological expertise, fluency in education policy, and the judgment to select the right method for a given question. Beyond individual expertise, the Director builds the systems and team capacity that keep Commit's analyses accurate, efficient, and accessible.
This job description is a summary and is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required of the employee.
The salary range for this role is $117,260-$143,318 annually.
Essential Duties and Responsibilities
Requirements
Qualifications, Skills, and Experience
Methodological Expertise
- Deep knowledge of quasi-experimental design, with a clear understanding of the tradeoffs between methods and of when a rigorous causal design is and isn't feasible.
- Fluency in mixed methods, pairing quantitative results with qualitative evidence to explain not just whether something works but why.
- Experience with broader statistical and data science methods, such as predictive modeling.
Research Judgment
- Sound judgment under uncertainty, offering well-reasoned recommendations when the data is imperfect or causal claims aren't possible, and being candid about the limits of the evidence while still supporting the decisions that have to be made.
- Ability to scope answerable research questions against the data and capacity actually available, and the intellectual honesty to report inconvenient findings.
Communication and Translation
- Strong ability to translate complex analysis into clear, actionable insights for technical and non-technical audiences alike.
- Exceptional written and verbal communication, including a sensibility for data visualization that makes findings legible at a glance.
Execution and Project Management
- Excellent…
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