Senior Strategy Analyst

About CPAL

At the Child Poverty Action Lab (CPAL), we believe every child deserves a life filled with opportunity. CPAL operates as an unofficial research and development lab for Dallas — using data to rethink public systems and equipping neighborhood-level partners to succeed, in service of one mission: cutting childhood poverty in Dallas by 50% within a single generation.

We work across five "big bets": Benefits Delivery, Maternal Health, Housing, Criminal Justice, and Public Safety. Each is grounded in evidence connecting childhood experience to adult economic outcomes.

Five design principles guide the work:

• Start with children and families, and work backward to systems.
• A problem well stated is half a solution.
• Systems are like a string of Christmas lights. One broken handoff takes the rest down.
• Have a bias for action. Perfect is the enemy of good.
• Test, learn, and iterate.

About the Role

Department: Strategic Analytics · Reports to: Head of Strategic Analytics

We're building a small, senior team of analytical generalists — people who've spent their careers answering hard, ambiguous questions for non-technical decision-makers, not building the systems that produce the numbers. If your last few years look like "a Big Bet lead handed me a fuzzy question and I went and found the answer in messy data," this role is built for you.

You'll take on questions that rarely arrive with clean data, a settled methodology, or even a well-formed problem statement — across housing, economic mobility, maternal health, education, and public safety. Deep prior expertise in any one of these isn't expected. What's expected is the instinct of a good consultant: frame the real question, get to a defensible answer fast, and know what to flag versus what to just decide and move on. The mindset is consulting rather than academic: get to a good answer fast, not a 100% answer too late.

This is not a data-engineering or pipeline-building role. You won't be maintaining dashboards or building the infrastructure that produces figures — you'll be the person a program lead calls when they need to know what the data actually says, by Thursday.

What You'll Do

• Take a fuzzy ask and turn it into an answerable question. Find the decision behind the request; decide what's worth measuring and what isn't.
• Work fast with imperfect data. Interrogate an unreviewed dataset before you build on it — most of the real risk in this job lives in data nobody has checked yet.
• Go beyond the literal ask. Say what else the requester needs to know, and what they shouldn't say publicly based on what the data can't support.
• Communicate like a consultant, not an academic. Turn analysis into a short, decision-ready brief (and a visual, where it helps) that a program lead can use in front of a reporter, a funder, or a city partner — today.
• Work AI-natively, and verify like it's your name on the answer. Use AI across research, coding, and QA — but the judgment, the framing, and the final synthesis have to be yours. AI drafts; you decide.
• Build institutional knowledge. Leave a trail — assumptions, sources, what you checked — so the next related question is cheaper to answer.

What Success Looks Like in Your First Year

• Your analysis has changed a resource-allocation decision, a program design choice, or an external message across more than one issue area.
• Program leads come to you with the ambiguous questions, not just the clean ones.
• Your AI-assisted workflows have made you faster without making your answers less trustworthy — you can always say what you checked and why.

Location

Dallas preferred; flexible for the right candidate. Remote-first candidates are considered, with occasional on-site time in Dallas.

Hiring Process

This role includes a short practical challenge — roughly 60 minutes total (analysis, a required visual, a written email, and a recorded video walkthrough). It uses a real, unreviewed data file and asks you to answer the kind of question a program leader would actually send you. You must complete the challenge to be considered.

Open to Sponsorship of Candidates

What We're Looking For

• A track record of answering questions, not just producing outputs. You can point to work that reads like "assessed whether X changed Y" or "determined whether X predicted Y" — not just "built the dashboard that shows Y."
• 3–5 years of applied analytical work, typically at a strategy, boutique data-science, or analytical consulting firm — or an equivalent unusual-early-responsibility trajectory (running analytics for a high-growth startup, agency, or civic org).
• Professional fluency in Python and working SQL; able to read and adapt existing R.
• A habit of communicating to a named non-technical audience — a program lead, a school administrator, a county department, a client — not only to other analysts.
• Consultant-style pragmatism: you pick the method that fits the question, the evidence, the timeline, and the stakes, and you can defend that choice.
• Daily working fluency with AI-assisted analytical tools, backed by concrete examples of when you overrode or corrected what the AI gave you.
• High agency and quick study across unfamiliar subject areas.
• A serious commitment to CPAL's mission. Prior nonprofit experience is not required.

Strong plus: geospatial analysis and data visualization experience; a background where a named method (a regression, a reliability coefficient, an effect size) was tied to an actual finding, not just listed as a skill.

Not a fit if: your experience centers on building and maintaining data pipelines, ETL/ELT, or BI dashboards without a track record of using that infrastructure to answer a specific analytical question — that's a different, and equally valuable, job. It isn't this one.

• Competitive salary commensurate with experience
• Health, dental, and vision insurance
• Retirement savings plan with employer match
• Generous paid time off and holidays
• Professional development and learning support
• Work with a small, senior team on problems that change outcomes for children and families in Dallas
• Direct access to program leaders and public-agency partners — your analysis reaches decision-makers, not a dashboard backlog
• AI-native ways of working actively supported and expected

CPAL is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law. If you need a reasonable accommodation at any point in the application or interview process, let us know and we will work with you to provide it.