Human Data Strategist

Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.

The Data Acquisition Team is responsible for ensuring that Reflection has all the data it needs to train the world’s best models. We're looking for a Human Data Strategist to own the pipelines that turn human expertise into better AI models. You will partner closely with researchers, deeply understand their needs, and source from vendors the data that improves our models’ usefulness and performance.

This role combines program ownership with hands-on work on task design, contributor workflows, data quality frameworks, and success metrics. The ideal candidate brings organizational rigor, technical curiosity, and sound judgment about when to move quickly and when to investigate the details.

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  Collaborate with research: Translate critical model capabilities, and researchers’ plans for developing them, into executable data acquisition strategies.

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  Orchestrate providers: Assess vendors’ capabilities, forecast capacity, define task instructions, acceptance criteria and then hold vendors accountable for quality, delivery, and cost.

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  Track and optimize campaigns: Build dashboards tracking throughput, turnaround time, acceptance rates, rework, and cost per accepted task. Leverage data analytics to investigate bottlenecks and guide improvements.

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  Ensure alignment: Experiments and priorities evolve. You will surface vulnerabilities early and turn feedback into concrete changes to subsequent sourcing. Work with research to close the loop; tracking how our data acquisitions improve model capabilities

• 4+ years of experience delivering a portfolio of complex programs and prioritizing across changing research needs.

• An understanding of LLM training, evaluation, and prompt design, with the ability to learn unfamiliar research concepts quickly.

• Proficiency in SQL for querying datasets and building dashboards, and Python for data analysis, API integrations, and workflow automation.

• Clear written communication, strong stakeholder judgment, and a willingness to inspect individual tasks and datasets when the headline numbers do not tell the full story.

• High agency, bias towards action, and the ability to drive impact in fast-paced, dynamic, and ambiguous environments

• Experience with annotation, expert data collection, human feedback, or AI evaluation is a plus.