Senior AI Data Scientist

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🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Chaos Labs

WebsiteLinkedInAll Job Openings

11 - 50 employees

🔒 Cybersecurity

₿ Crypto

Cybersecurity • Crypto

Chaos Labs is a cloud platform for securing blockchains and protocols through robust agent and scenario-based simulations. It addresses the technical challenges and security vulnerabilities inherent in decentralized blockchain applications, especially in the burgeoning decentralized finance (DeFi) space. By enabling teams to conduct high-fidelity simulations on mainnet forks, Chaos Labs provides a real-world testing environment that enhances development speed while ensuring the security of protocols. Focused on developer tooling and cloud infrastructure, it accelerates the go-to-market time for blockchain protocols, with current support primarily for the Ethereum network and plans for expansion to others like Terra, NEAR, and Polygon.

📋 Description

• Design and build machine learning systems powering enterprise search, retrieval, recommendations, and AI agents • Develop evaluation frameworks and metrics for LLM-powered application quality, performance, and business impact • Build scalable data and ML pipelines for large-scale AI interaction data • Apply statistical modeling, experimentation, and causal inference to guide product development and strategic decisions • Collaborate with Product, Engineering, and Design to translate research and insights into production features • Analyze product usage and customer behavior to improve AI adoption, productivity, and user experience • Prototype, evaluate, and deploy AI capabilities using foundation models, embeddings, and retrieval-augmented generation techniques • Define key performance indicators and analytical frameworks for product strategy and company-wide decisions • Identify opportunities to leverage machine learning and generative AI in the AI platform • Mentor junior team members and establish data science, experimentation, and machine learning best practices

🎯 Requirements

• 5+ years of experience in Data Science, Applied Machine Learning, or quantitative research, or 3+ years with a PhD • Degree in Computer Science, Statistics, Mathematics, Machine Learning, Economics, Physics, or another highly quantitative field • Strong proficiency in Python and SQL • Experience building scalable data and ML pipelines • Deep understanding of statistics, experimentation, causal inference, and predictive modeling • Experience developing and deploying machine learning models in production • Experience working with large-scale datasets and modern data infrastructure • Familiarity with LLMs, embeddings, retrieval systems, RAG, or AI agents • Ability to translate ambiguous problems into measurable solutions • Excellent communication skills and ability to work cross-functionally with engineering, product, and leadership • Comfortable operating in a fast-paced, high-ownership startup environment • Based in NYC with ability to work from the Brooklyn office, or able to work remotely • For remote work, based within the U.S. and able to travel up to 30% of the year for team collaboration • Preferred: experience building or evaluating LLM-powered products or AI applications • Preferred: background in search, recommendation systems, information retrieval, or knowledge graphs • Preferred: experience designing A/B tests, offline evaluations, and ML benchmarking frameworks • Preferred: familiarity with vector databases, embedding models, and agent orchestration frameworks • Preferred: contributions to open-source ML projects or publications in machine learning, NLP, or related fields • Preferred: experience in B2B SaaS, developer tools, or enterprise AI products

🏖️ Benefits

• Compensation & Equity – competitive package aligned with growth, performance, and merit • Career Growth Opportunities – be part of a rapidly expanding, global technology company with room to grow professionally