Senior Data Scientist

Role Overview

Senior Data Scientist to lead empirical research on blockchain protocols, MEV, and market structure, informing Optimum’s networking products and analytics strategy.

Responsibilities

• Own empirical research on MEV, block building, orderflow, validator/proposer behavior, latency-sensitive execution, and related market-structure dynamics.
• Work with on-chain and network datasets (e.g., Xatu) including mempool, relay, validator, and network-level timing data.
• Convert open-ended research questions into rigorous analysis, clear conclusions, and product-relevant recommendations.
• Use an atomic, hypothesis-driven approach:
  • Formulate hypotheses
  • Define verifiable tests
  • Evaluate evidence rigorously
  • Translate findings into actionable decisions
• Design and evaluate experiments, measurements, and causal analyses for latency-sensitive blockchain systems.
• Build analytical frameworks to distinguish signal vs noise in complex, high-variance settings.
• Develop predictive/statistical/simulation-based models to answer concrete product and strategy questions.
• Document assumptions, limitations, methodology, and results with high rigor.
• Partner with Product, Research, Economics, and Engineering to translate findings into product direction and customer-facing primitives.
• Collaborate with Engineering on data pipelines, evaluation tooling, and production-ready research infrastructure.
• Communicate complex insights clearly to technical and non-technical stakeholders.

Requirements

• 5+ years in quantitative research, empirical data science, or a similarly analytical role (ideally crypto/market structure/distributed systems/latency-sensitive systems).
• Strong statistical background and experimental rigor; ability to design and interpret experiments such as A/B testing, causal inference, quasi-experiments, diff-in-diff, and instrumental variables.
• Deep blockchain empirical research experience, ideally with Ethereum (or another major L1/L2), including hands-on MEV/block building/orderflow/validator-proposer dynamics and transaction propagation.
• Experience building predictive and analytical models using regression, classification, time-series analysis, and modern machine learning.

Nice-to-haves

• Experience designing experiments and causal analyses specifically for latency-sensitive blockchain systems.
• Familiarity with network-level timing signals and building simulation-based models for product strategy.