Senior Strategy Analyst

Provn, Inc.; Dallas (TX); Hybrid; USD 90,000 - 130,000; Full time

Job summary

CPAL seeks a senior analytics generalist to answer hard, ambiguous questions for non-technical decision-makers across housing, mobility, maternal health, education, and public safety. You’ll frame the real question, work with imperfect data, and deliver decision-ready insights by end of day, with a consulting mindset rather than academic rigor.

Onsite in Dallas preferred, remote optional. This is not data-engineering; you’ll synthesize findings, flag risks, and build institutional knowledge to

Qualifications

• Senior analytics generalist experienced in answering hard, ambiguous questions for non-technical decision-makers.

Responsibilities

• Take ambiguous asks and turn them into answerable questions.
• Work fast with imperfect data and deliver decision-ready insights by EOD.
• Communicate like a consultant, not an academic, with concise briefs and visuals.

Job description

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

Onsite preferred but open to remote with occasional office presence for the right candidate

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 senior leader handed me an ambiguous 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 EOD.

What You’ll Do

• Take an ambiguous 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*