• Frame business requirements and objectives as succinct data science problems • Extraction, cleaning and transformation of relevant data for different Integrated Customer Experience Problems for analysis, modelling and reporting • Implement and deploy robust, state-of-the-art analytics and machine learning models across the Ajua Product Stack, directly impacting merchants and enterprise customers • Work with product teams to translate product feature requirements and use cases into experiments, and lead with the design, development, analysis and reporting of results, leading to decisions that directly impact customers • Actively pursue improving data science skills, including but not limited to problem-solving, writing readable/testable/efficient code, mastering Integrated Customer Experience Data, and learning to anticipate Customer and Data related product issues and needs • Actively participate in internal Data Science and broader technology project reviews and participate in community meet-ups • Collaboratively work with the engineering, products, and customer success teams and communicate clearly and effectively regardless of seniority

• Partner closely with our clients' executive and technical teams to guide decisions relating to AI, analytics, data engineering and data in general • Proactively identify and champion projects that solve complex problems across multiple domains • Apply specialized skills and fundamental data science methods (e.g. experimental design, recommender systems and machine learning when needed) to inform improvements to clients' businesses • Design and implement end-to-end data pipelines: work closely with stakeholders to build models, tables or schemas that support business processes • Empower teams both internal and external to build and maintain actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products

• 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.