• Partner with technical and business leaders to design key metrics, dashboards, and AI-enabled data products that are widely-adopted and influence cross-functional strategic direction and multi-year roadmaps • Establish hypothesis-driven decision-making as the default operating mode across partner teams through statistically rigorous experimentation • Tackle undefined, open-ended problems by defining both the 'what' and 'how' and conducting rigorous analyses that drive meaningful product and business impact • Transform complex findings into compelling narratives that provide strategic clarity and influence broader organizational direction • Collaborate closely with Data Engineers to influence the design, development, and maintenance of dimensional data models, ensuring data is complete, accurate, and reliably delivered • Champion world-class data governance practices, continuously raising the bar for data & code quality across technical teams • Partner with stakeholders to align roadmaps with business priorities, anticipating emerging needs before they are formally requested and driving positive outcomes in high-stakes contexts • Operate as a force multiplier whose influence fosters growth across partner teams, providing incisive technical mentorship, inspiring intellectual curiosity, and driving clarity amidst ambiguity

• Build and deploy predictive models for operational planning and execution (e.g., cycle time, throughput, labor/time estimation, service levels) • Develop and improve optimization and decision algorithms (e.g., routing, replenishment, inventory positioning, parameter estimation) • Design experiments and evaluation frameworks to validate impact (accuracy, latency, cost reduction, productivity lift) • Translate business workflows into model-ready problem statements, features, and measurable success criteria • Partner with software engineers to ensure solutions are production-ready (reliable inference, monitoring, versioning, performance tuning) • Create clear documentation and stakeholder-ready summaries of methodology, assumptions, and results • Contribute to architecture and scaling decisions for data/ML solutions (performance, robustness, and maintainability)

• Work closely with the co-founding team to provide a solid analytical foundation for buyVerde’s mission-critical efforts in data acquisition, enhancement, and awareness • Conduct exploratory data analysis, customer segmentation, and evaluate the quantitative impact of key business decisions • Develop and tune models to organize, enhance, and expand buyVerde’s core data asset • Create metrics and a visual dashboard to track buyVerde's growth versus targets • Responsible for KPI metrics dashboard and monitoring across various categories and business areas including product catalog, vendor relations, user behavior, and sales • Operate and improve buyVerde's Standards Board Review process to verify vendor ESG data • Use scripting, SQL, and low-code tools to streamline product for non-technical business users • Develop automated capabilities to enrich buyVerde's data with ESG values and improve named entity recognition capabilities

• Translate product requirements to machine learning problems and identifying areas where AI can have the most business impact; • Analyze data to identify significant patterns and generate actionable insights; • Perform exploratory data analysis EDA and feature engineering to support the modeling process; • Apply best practices on model selection, parameter tuning etc.; • Run comparative experiments for model training; • Analyze ML metrics to evaluate different potential solutions; • Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production environments; • Mentor and guide junior members, sharing knowledge and leading complex projects.