LMArena

Data Scientist

• 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 clearly to technical and non-technical partners, informing both research direction and infrastructure improvements.

Senior Data Scientist

Technical Recruiter

• Partner with hiring managers to clarify role outcomes, success profiles, and interview plans; prioritize reqs against business goals
• Run full-cycle recruiting: kickoff → JD refinement → sourcing → assessment → debriefs → offer → close
• Build pipelines via targeted sourcing (passive outreach, talent communities, events, referrals, and job posts)
• Maintain a structured, fair process: define competencies, calibrate rubrics, and uphold consistent candidate experience
• Track and improve funnel health (speed, quality, diversity signals); report weekly and quarterly progress with metrics and narrative
• Drive offer strategy and negotiations aligned to leveling, compensation bands, and market insights
• Nurture long-term networks of high-potential talent and keep a mapped bench for critical and future roles
• Partner on employer brand moments (events, content, communities) to attract deep-tech talent
• Coach hiring managers and interviewers on best practices and candidate excellence

Machine Learning Engineer

• Lead open-source ML research including open data set and code releases to advance AI model evaluation in the open.
• Design, run, and share new methods and experiments revealing what makes models useful, trustworthy, and capable, grounded in human preference signals and released openly for the ecosystem and research community to build upon.
• Take commitment to openness from principle to practice; curate high-impact datasets; develop new methodology and reproducible benchmarks; release code enabling the research ecosystem to push AI evaluations forward.
• Shape the public leaderboard, power community tools, and strengthen transparency in AI evaluation worldwide.
• Work interdisciplinary with engineers, product teams, marketing, and the broader research community to advance how we compare models, analyze preference data, and understand factors like style, reasoning, and robustness.
• Collaborate with GTM teams as spokesperson for outreach for our open research efforts: strengthening partnerships, expanding research community participation, and championing programs that grow and support our research network.
• If you’re excited by open-ended questions, rigorous evaluation, and scientific communication and outreach, you’ll find a meaningful home here.

Senior Data Scientist

Technical Recruiter

Machine Learning Scientist - Open Source Lead