• Own competitor intelligence across Trust Wallet's core verticals: swap & DEX aggregation, earn & staking, and wallet market share — tracking protocol metrics, user behavior, and market dynamics on a regular cadence • Monitor on-chain activity across EVM chains (BNB Chain, Ethereum, Base, Arbitrum and others) and identify trends relevant to Trust Wallet's product, growth, and strategy • Follow the crypto ecosystem on X and translate market discourse and emerging narratives into concrete data questions worth answering • Build dashboards and analyses that connect on-chain signals with Trust Wallet's product context • Collaborate with the internal data team to enrich internal metrics with ecosystem-level perspective • Brief leadership on significant on-chain developments with clear, non-technical narrative

Leverage technical expertise to transform client data into actionable insights while delivering strategic plans for data integration and quality. Mentor team members and assess data management technologies to bridge gaps in client solutions.

• Provide analytic data to support our annual sales planning including quota planning, go-to-market modeling, capacity modeling and optimization • Convert raw data into well-presented and useful business information that drives business decisions • Drive standards of performance and specific activities that align with the predefined success criteria for the sales organization; track and report on these activities to ensure outcomes are on track/met • Track regularly the metrics on general business performance, average discounts, non-standard exceptions, etc., recommend action items for improvement

Role Description - Strong Python and Jupyter notebook experience with heavy use of Pandas for joining, reshaping, aggregating, and validating multiple data frames. Experience with NumPy and SciPy statistics is highly preferred. - Hands-on experience building Monte Carlo simulations including distribution selection and fitting, sampling design, and interpreting P10 P50 P90 results. Experience handling correlated variables is a plus. - Experience converting complex Excel models into code by tracing formulas, documenting assumptions, and validating numeric accuracy. - Ability to build reliable data pipelines in Python including API authentication, pagination, schema normalization, error handling, and incremental refresh. - Strong SQL skills for extracting inputs from data warehouses or billing databases. - Experience with versioning and auditability beyond Git, including structured snapshot storage of inputs and outputs. - Comfort explaining model outputs and variance drivers to non-technical stakeholders and producing business-ready commentary. Qualifications - Prior work in FP&A, cloud economics, FinOps, or cost and usage modeling for AWS, Azure, or GCP. Company Description