• Analyzing billions of blockchain wallets and tens of billions of transactions to derive actionable insights • Developing and refining both descriptive statistics and predictive models • Collaborating closely with engineers and product teams to develop models that drive data-driven decisions • Enhancing our product offerings and identifying new growth opportunities • Optimizing models for performance and cost in distributed data warehouses • Conducting data mining on public data to extract actionable insights • Managing ETL connectors to ensure seamless data flow across systems • Guiding the development of visualizations to present data findings in an intuitive and accessible manner

• Help develop KoBold’s proprietary software exploration tools. • Find and curate geophysical, geochemical, geologic, and geographic data and integrate it into KoBold’s proprietary data system. • Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth’s crust. • Create effective visualizations for evaluating model performance and enabling rapid interaction with the underlying data and key features. • Develop and apply data processing, statistical, and physics-based techniques to geoscientific data — from computer vision to geophysical inversions — and use the results to guide our targeting efforts and inform our acquisition and exploration decisions. • Present to and collaborate with our external partners and stakeholders.

• Build and train our next generation AI platform. • Collaborate with a diverse team of designers, developers, engineers and data scientists. • Focus on building and training robust and interactive machine learning applications. • Communicate and present work in a clear and simple manner as a strong team player.

• Lead the Experimentation Roadmap • Design, implement, and rigorously analyze complex A/B tests • Apply advanced causal inference techniques • Conduct complex, proactive, and exploratory analysis • Define, instrument, and govern a unified Key Performance Indicator (KPI) framework • Partner with Data Engineering to design and build scalable, self-serve experimentation tooling • Translate complex statistical findings into clear business narratives • Train and mentor junior and mid-level data scientists