• You will serve two primary functions: (1) designing and performing analyses that help the Economics and Executive Leadership teams make informed, data-driven decisions, and (2) building and maintaining systems for the parameterization of production applications. • You will work on a wide array of blockchain economics projects, analyses, and systems, including: • Designing novel mechanisms and incentive schemes • Building models and simulations to evaluate investment opportunities • Designing and parameterizing trading systems • Optimizing parameters for production applications • Contributing to the design of Economics programs and applications • You will optimize network incentives and systems by engaging directly with the Economics, Product, Engineering, Research, and Data Science teams to understand network dynamics at the deepest level. • You will meticulously operationalize processes, and coordinate cross-functionally to implement them. • This is both a highly technical and highly social role. You will have high visibility and a large impact on how Chainlink builds the world’s first fully sustainable decentralized oracle network.

• Develop and maintain dashboards, scorecards, and data visualizations using tools such as Tableau, Power BI, or similar platforms. • Use SQL, Alteryx, Python, or other analytics tools to manage, transform, and analyze complex datasets. • Apply AI/ML techniques (e.g., predictive modeling, clustering, NLP, forecasting) to support business decision‑making and uncover new opportunities. • Automate manual processes and build scalable, repeatable data workflows that improve efficiency and data quality. • Collaborate with cross‑functional partners to gather requirements, translate business needs into analytical solutions, and adapt to shifting priorities. • Communicate insights clearly and effectively to technical and non‑technical stakeholders through presentations, reports, and data storytelling. • Contribute to the design and enhancement of data platforms, analytics processes, and governance practices. • Mentor junior analysts and support the development of best practices across the analytics team.

• Conduct in-depth product analytics to uncover user behavior patterns and trends • Analyze web data, conversion funnels, and user journeys to identify optimization opportunities • Perform ad hoc analyses to answer critical business questions and support strategic decisions and monitor key performance metrics and proactively identify areas for improvement • Investigate user engagement patterns to enhance product stickiness and retention • Collaborate with cross-functional teams to solve complex business problems • Create intuitive and powerful dashboards in Hex and Looker for stakeholders across the organization • Develop comprehensive reporting frameworks aligned with company KPIs • Measure the success of new product features through rigorous data analysis • Establish metrics that accurately reflect product health and business impact • Automate reporting processes to increase efficiency and data accessibility • Independently lead the statistical, direction of our experimentation agenda, guiding the business on experimentation and statistics best practices, dig into confounding factors and prioritizing designing complex experiments including pricing experiments • Lead experiment design and execution and build a strong experimentation culture by educating teams on best practices • Apply statistical rigor to test design, sample size determination, and results interpretation • Identify opportunities for A/B testing to optimize product performance • Use tools like Optimizely, Eppo, or LaunchDarkly to implement and track experiments • Develop frameworks for consistent and reliable experimentation across the company • Influence stakeholders by translating complex data findings into compelling stories • Build clear, concise presentations to executive teams that drive action • Find innovative ways to quantify ambiguous business problems • Advocate for data-informed approaches to solving business challenges • Proactively identify opportunities where data can drive business value

• Conduct in-depth analysis using the data warehouse to identify trends, patterns, and insights. • Interpret complex data sets and communicate findings to both technical and non-technical stakeholders. • Assist with ETL processes to extract, transform, and load data from various sources. • Collaborate with IT teams to create seamless data integrations. • Perform thorough data validation and testing to ensure the highest possible data quality. • Clearly define and communicate when quality standards are not being met. • Perform root cause analysis to identify the underlying or fundamental causes of an issue or problem. • Work closely with cross-functional teams, including IT and business stakeholders, to align on goals and key deliverables. • Accurately document data mappings and definitions.