via Ashby
$0K - 0K a year
Providing technical support and troubleshooting for enterprise storage, networking, and systems, mentoring junior staff, and collaborating with engineering teams.
Extensive experience in technical support, troubleshooting, and enterprise IT environments, with skills in Windows, Linux, VMware, SAN/NAS, and scripting.
About the Role As a Senior Data Scientist you’ll explore and reason about the data that powers millions of AI evaluations each week. You’ll generate and test hypotheses, identify causal relationships, and uncover insights that help us understand how frontier models behave in the real world. You’ll collaborate with ML researchers and engineers to design experiments, analyze large-scale datasets, and build statistical frameworks that improve the reliability and interpretability of our AI evaluation systems. You’ll Explore and analyze large, complex datasets to uncover patterns, biases, and causal relationships in model behavior and system performance. Formulate hypotheses about data quality, evaluation outcomes, and model performance — then design experiments to validate or refute them. Build reproducible analysis pipelines using Python, Pandas, NumPy, and Spark to process and interrogate large-scale data. Partner with ML researchers and engineers to design metrics and analyses that evaluate how models perform across domains, prompts, and tasks. Develop causal reasoning frameworks and statistical methods that help explain why models behave as they do — not just how well they perform. Communicate insights (for example, via blog posts) clearly to technical and non-technical partners, informing both research direction and infrastructure improvements. You’ll have 6+ years of experience in data science, ML analytics, or applied research, preferably in AI, ML, or large-scale data environments. Strong proficiency in Python, with deep experience in Pandas, NumPy, and distributed frameworks like Spark. Expertise in statistical modeling, causal inference, and experimental design. Experience reasoning about data distributions, sample quality, and the effects of data distribution shifts. Strong communication skills and the ability to collaborate closely with ML researchers and engineers. (Bonus) Background in AI model evaluation. (Bonus) Experience working with LLM outputs (for example, LLM-as-a-judge), embeddings, or other large-scale model artifacts. (Bonus) Experience with A/B testing. What we offer The cash compensation for this position has not yet been finalized. Actual compensation will depend on job-related knowledge, skills, experience, and candidate location. Competitive salary and meaningful equity Comprehensive healthcare coverage (medical, dental, vision) The opportunity to work on cutting-edge AI with a small, mission-driven team A culture that values transparency, trust, and community impact
This job posting was last updated on 12/19/2025