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Senior Strategy Analyst

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Provn, Inc.
Full Time position
Listed on 2026-08-26
Job specializations:
  • Business
    Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 90000 - 130000 USD Yearly USD 90000.00 130000.00 YEAR
Job Description & How to Apply Below

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*

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Position Requirements
10+ Years work experience
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