Data Scientist - ML Research

Arena; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Equity

Health benefits

Job summary

Candidates should have extensive Python expertise, experience with Spark, and a track record in data science or applied ML research within AI contexts. The position offers a competitive compensation package and equity.

Qualifications

• 6+ years of experience in data science, ML analytics, or applied research.
• Strong Python skills with Pandas and NumPy.
• Experience with distributed processing frameworks like Spark.
• Expertise in statistical modeling, causal inference, and experimental design.
• Ability to communicate insights to both technical and non-technical audiences.
• Bonus: Background in AI model evaluation.
• Bonus: Experience with LLM outputs, embeddings, or other large-scale model artifacts.
• Bonus: Experience with A/B testing.

Responsibilities

• 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.

Skills

Data science

ML analytics

Applied research

Python

Pandas

NumPy

Spark

Statistical modeling

Causal inference

Experimental design

Communication

LLM evaluation

AI models evaluation

Tools

Spark

Job description

About Arena Intelligence

Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it.

About Arena Intelligence

Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it.

Tens of millions of people use Arena each month to evaluate how frontier systems handle the work they actually do. The preferences they share power the most transparent, rigorous, and human-centered evaluations in AI. Leading AI labs, enterprises, and independent researchers rely on our work and open datasets to understand how models behave in real workflows: agentic coding, creative generation, professional productivity, and beyond. We go beyond leaderboards and decompose what human experience reveals about AI, so models advance toward the work people actually do.

We're a team of researchers, academics, builders, and creatives from UC Berkeley, Google, Stanford, and DeepMind. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We're building a company where thoughtful, curious people from all backgrounds can do their best work together, in an office culture that radiates excellence, energy, and focus.

About The Role

As a 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. We are considering candidates who are senior level or higher for this role.

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

• We offer competitive compensation and equity aligned to the markets where our team members are based. The base salary range will depend on the candidate’s permanent work location.
• Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs.
• The opportunity to work on cutting-edge AI with a small, mission-driven team
• A culture that values transparency, trust, and community impact
  
  

Come help build the space where anyone can explore and help shape the future of AI.

Arena Intelligence provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.