Senior Strategy Data Scientist

About the role

Senior Strategy Data Scientists at CPAL take on questions that rarely arrive with clean data, a settled methodology, or even a well-formed problem statement. You'll work out what decision needs to be made, what evidence would actually be useful, and how to deliver value without overengineering the solution.

CPAL, the Child Poverty Action Lab, operates as an unofficial research and development lab for Dallas, using data to rethink public systems and equip neighborhood-level partners, all in service of one mission: cutting childhood poverty in Dallas by 50 percent within a single generation. This role sits on CPAL's Strategic Analytics team, reporting to the Head of Strategic Analytics, on a small, senior team built to combine analytical rigor, practical judgment, and AI-enabled ways of working as a strategic thinking partner for CPAL's program teams.

You'll work across housing, economic mobility, maternal health, education, and public safety, conducting analysis end to end: combining messy data, selecting the right method, testing findings, and documenting sources, assumptions, and limitations so the next related question is cheaper to answer.

Requirements

• 3 to 5 years of applied analytical work, typically at a top-tier strategy, boutique data science, or analytical consulting firm, or an equivalent trajectory with unusual early responsibility, running analytics for a high-growth startup or agency.
• Strong quantitative foundation, with a STEM degree, an applied quantitative social science background in economics, urban science, spatial analytics, operations research, or causal inference and program evaluation, or comparable demonstrated capability.
• Professionally fluent in Python with working SQL, and able to read and adapt existing R.
• 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 real examples.

Benefits

• Direct access to program leaders and public-agency partners, where your analysis reaches decision-makers instead of a dashboard backlog.
• AI-native ways of working are actively supported.
• Competitive compensation dependent on experience.
• Flexible work posture: Dallas-preferred, with remote-first candidates considered for the right fit (occasional on-site time in Dallas required).
• Visa sponsorship available.

Applications close September 14, 2026.