Senior Strategy Data Scientist

Senior Strategy Data Scientist CPAL (Child Poverty Action Lab) Dallas, TX · Full-time

Strategy questions here rarely arrive clean. No settled methodology, no well-formed problem statement, just a decision that needs to get made. This role turns messy analysis into decisions that redirect real resources for kids and families in Dallas.

At the Child Poverty Action Lab, 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. One mission drives all of it: cutting childhood poverty in Dallas by 50% within a single generation. Five big bets carry that mission forward: Benefits Delivery, Maternal Health, Housing, Criminal Justice, and Public Safety, each grounded in evidence connecting childhood experience to adult economic outcomes.

Five design principles guide the work. Start with children and families, then work backward to systems. A problem well stated is half a solution, so systemic issues get made concrete, actionable, and replicable before anyone tries to fix them. Systems are like a string of Christmas lights: one broken handoff, missing data, a confusing process, takes the rest down, and finding it is a repeatable exercise. Have a bias for action. Perfect is the enemy of good, so the team moves on the best available information rather than waiting for certainty. Test, learn, iterate. Experiment fast, build feedback loops, amplify what works.

This role sits on Strategic Analytics, reporting to the Head of Strategic Analytics. The team exists to find leverage: turning data into insight that helps CPAL and its partners direct limited resources where they'll improve the lives of the most children. It's small and senior, built to combine analytical rigor, practical judgment, and AI-enabled ways of working into a genuine strategic thinking partner for the program teams on the ground. Based in Dallas, TX. Onsite is preferred, but CPAL will consider remote-first candidates with occasional time on site.

Senior Strategy Data Scientists take on questions that rarely arrive with clean data, a settled methodology, or even a well-formed problem statement. You work out what decision needs to be made, what evidence would actually be useful, what can credibly be answered, and how to deliver value without overengineering the solution. Consulting, not academic. Get to a good answer fast, not a 100% answer too late. The areas span housing, economic mobility, maternal health, education, and public safety. Deep expertise in all of them isn't the bar. Learning fast is: picking up unfamiliar domains quickly, working confidently with imperfect data, and communicating sophisticated ideas clearly to non-technical decision-makers.

Day to day, you conduct analysis end to end: combining messy data, selecting appropriate methods, testing findings, documenting sources, definitions, assumptions, and limitations. You frame the question before you analyze it. That means finding the decision behind the request, then defining the smallest useful first version. And you go past the literal answer: explaining what the result means, surfacing adjacent insights, raising the questions stakeholders didn't know to ask. Each output gets built to be reusable, so the next related question is cheaper to answer. You work AI-natively too, using AI across research, coding, QA, and documentation. But you verify it carefully. Trusting it blindly isn't the job.

You fit if you bring a strong quantitative foundation. A STEM degree works, so does an applied quantitative social science background, economics, urban or spatial analytics, operations research, causal inference and program evaluation, population health analytics, or comparable demonstrated capability. Add 3 to 5 years of applied analytical work, typically at a top-tier strategy, boutique data science, or analytical consulting firm. An equivalent trajectory with unusual early responsibility, running analytics for a high-growth startup or agency, fits too.

You're professionally fluent in Python and working SQL, and you can read and adapt existing R. What separates a strong applicant here isn't the tool list. It's sound methodological judgment paired with consultant-style pragmatism: picking the approach that fits the question, the evidence, the timeline, and the stakes. Daily working fluency with AI-assisted analytical tools, backed by concrete examples, is part of that same judgment. High agency and intellectual curiosity matter. So does a serious commitment to CPAL's mission, more than prior nonprofit experience does, which isn't required. Geospatial analysis and data visualization experience is a strong plus.

How hiring works here

Referrals are king for getting an interview. But what if you don't have a referral? Applying with Provn is designed to help you get more interviews. Instead of sending a cold resume into an ATS and waiting, you will complete a challenge built by CPAL and submit a short video walking through your approach. No time limit. No timers. No restrictions on AI usage. Show how you build with AI.

Why that works in your favor:

• You show how you actually build and ship with coding agents, instead of hoping a resume communicates your skill clearly.
• Your judgment with AI becomes visible, which no "proficient with AI coding agents" resume bullet can prove.
• One challenge puts you in front of the strategic analytics team, scored on the work. Priority without a referral!

The hiring manager reviews every completed submission, and strongest candidates go straight to an interview round. No referral needed. Performance over pedigree. Proof over polish.

For this role, the challenge is a significant part of your candidacy. Only completed applications that include the challenge submission will be considered.

The challenge itself runs roughly 45 minutes: 30 minutes of analysis, plus a written email and a recorded video walkthrough. It's built around a real, unreviewed data file, the kind of question a program leader at CPAL would actually send.

CPAL is open to sponsoring the right candidate.

Compensation for this role is competitive, dependent on experience. Benefits include health, dental, and vision insurance, a retirement savings plan with employer match, generous paid time off and holidays, and professional development and learning support. You'll 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 comes with it, so your analysis reaches decision-makers, not a dashboard backlog. AI-native ways of working: actively supported, actively expected.

CPAL is an equal opportunity employer and considers 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, CPAL will work with you to provide it.