Senior Strategy Analyst

Child Poverty Action Lab (CPAL)|Dallas, TX|Full time|Hybrid|Applications close October 18 About CPAL Every child deserves a life filled with opportunity. CPAL operates as an unofficial research and development department for Dallas, rethinking how data can be integrated into public systems, community programs, and neighborhood life to break cycles of intergenerational poverty. The mission is specific and measurable: cut child poverty in Dallas by half within a single generation. Child poverty is a problem of a scale that only public budgets can fund solutions to match, so CPAL convenes the leaders of nine Dallas public agencies with a combined annual operating budget of more than $10 billion, alongside more than 100 partner organizations, and points those resources at the interventions evidence supports. The work spans five big bets: Benefits Delivery, Maternal Health, Housing, Criminal Justice, and Public Safety. About the role The Senior Strategy Analyst is a consultative role rather than an academic or reporting one. We are not looking for a data scientist to build machine learning pipelines or architect databases. We are looking for someone who can get to a defensible answer quickly, under real-world time pressure, and who knows when the answer approximates truth well enough to act on. You will work with independence and judgment, while collaborating closely with internal teams and community partners. Requests reach you from city officials, agency heads, and foundation leads as broad questions, and the data that could answer them is usually public, messy, and unreviewed. Your job is to find the decision behind the request, establish what is measurable, and produce an answer a leader can use. A problem well stated is half a solution. Questions that land on this desk look like these: Where are the most people eligible for SNAP benefits but not accessing them? Where should a mobile clinic set up to improve access to contraception? Are students who live further from school more likely to be chronically absent, and what might a school do about it? Who gets evicted, how often, and what interventions might change the pattern? What you'll do Expect most requests to come from someone with a decision to make and a short timeline. The job is determining which question actually needs to be worked, establishing what the available data can support, and delivering something non-technical leaders can act on and defend in public. Turn a fuzzy ask into an answerable question. Find the decision behind the request, isolate what is measurable, and define the smallest useful first iteration instead of getting bogged down in endless analysis. CPAL starts with children and families and works backward to systems, which is what keeps an analysis attached to what a family experiences on the ground. Conduct applied data analysis using publicly available and administrative datasets. ACS, CDC WONDER, Department of Education, criminal justice data, TX HHSC, Dallas ISD, Feeding America, internal program data, and others, with a working understanding of their quirks: complex sampling, vintage issues, sample weights, missingness, and outliers. Interrogate an unreviewed dataset before you build on it, because most of the risk in this job lives in data nobody has checked yet. Trace a system to the point where it breaks. CPAL views public systems like a string of Christmas lights, where one dropped notification or missing form takes the rest of the line down. Follow a multi-agency workflow to where families fall out of it, then say what that means for budgets, policy levers, and operations, including where dollars and frontline staff should go next. Go beyond the literal ask. Tell the requester what else they need to know, flag the confounders, and say plainly what they should not claim publicly because the data will not support it. Translate findings into clear, responsible communications for stakeholders who are not statisticians. Help them understand what the data supports and what it does not. Communicate like a consultant, not an academic: a one-page memo or brief, with a visual where it helps, that a program lead can use in front of a reporter, a funder, or a city partner today, and that reads for a city council member, police leadership, a hospital director, or a community organizer. Clarity over aesthetic flair. Work AI-natively, and verify like it is your name on the answer. Use AI across research, coding, and QA. The framing, the judgment, and the final synthesis stay yours. AI drafts; you decide. Produce clean, well-documented, reproducible workflows. Record your assumptions, sources, and what you checked, so your work can be understood, audited, and built on by others, and 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 in more than one issue area. That might be a housing affordability analysis becoming the fact base a city partner argues from, or an enrollment gap that sends outreach to a few neighborhoods instead of the whole city. Program leads bring you 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 This role is based in Dallas and works hybrid, with regular time in the office alongside the team and CPAL's public-agency partners. CPAL is open to sponsoring candidates. What we're looking for More than anything, we are looking for a particular kind of analytical instinct. Can you defend your choice of denominator when there were three reasonable options? When a tract-level estimate carried a margin of error wide enough to swallow the difference someone was asking about, did you aggregate up, caveat hard, or tell them the comparison could not be made, and can you walk another person through why? We want someone who has made calls like that and can explain them. 3 to 4 or more years of applied experience using data to answer real-world questions. Not just running models, but knowing which model to run and why. Fluency in at least one analytical programming language: R, Python, Stata, or similar. Reproducible, well-commented code is a must. Hands‑on experience with complex, publicly accessible and administrative datasets, and a genuine understanding of what makes each one tricky. Strong grounding in statistical methods: regression, sampling and weighting, hypothesis testing, missing data, and the limits of each. The ability to work fast under pressure and to know when an answer is good enough to act on, without cutting the corners that matter. Strong written and verbal communication, including the ability to explain methodological decisions to non-technical audiences. A commitment to using data for good, carefully, transparently, and in service of communities. Bonus if you have Experience with program evaluation, quasi-experimental design, or causal inference methods. Familiarity with geographic or spatial analysis. Poverty in Dallas is highly localized, and neighborhood‑level work runs through it. Experience in a nonprofit, government, or policy‑adjacent environment, including the lags and quirks that come with public records. Comfort with AI‑assisted research workflows: prompt engineering, LLM‑assisted coding or thematic analysis, and output validation. Benefits and perks Salary of $100,000 to $140,000, 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, so your analysis reaches decision‑makers rather than 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. #J-18808-Ljbffr Provn