Afresh

• Own and execute integration projects from customer discovery through go-live — creating detailed project plans with milestones, risk mitigation, and success criteria, and coordinating internal and customer-facing stakeholders through each phase • Lead technical discovery and design engagements with customers, including multi-day on-sites where you independently scope 10–15 data interfaces, negotiate delivery timelines and formats, and leave with documented data integration specifications that power ML model training and deployment • Apply deep knowledge of Afresh's core data model and integration patterns to evaluate whether customer needs can be met through standard approaches; flag misalignments and propose adjustments to design or the customer's approach • Analyze complex data relationships, identify root causes of mismatches or anomalies, and build custom queries or lightweight tools to streamline validation and data mapping work • Collaborate with data engineering, product engineering, and data science to drive integration delivery; surface technical risks and ambiguities early and work cross-functionally to resolve them • Influence internal discussions with thoughtful input and context from customer needs; share learnings across Product, Sales, and Customer Success • Contribute to team documentation, templates, and onboarding content; mentor junior team members and take initiative on process improvements

• Lead accounting operations and the team. • Own a fast, reliable month-end close — and make it faster with AI. • Modernize AP, AR, and expense workflows. • Deliver financial reporting and insight. • Own revenue recognition and technical accounting. • Lead audit readiness. • Manage payroll, tax, treasury, and compliance. • Partner across the business.

• Own end-to-end design for a web application for corporate users who own the grocery replenishment function, spanning ordering, exceptions, configuration, and performance. • Design reporting, insights, and performance dashboards, from table stakes today toward conversational, AI-powered analytics. • Design exception-based workflows and controls (ordering, display size, configuration, order policy tuning) that let corporate users manage operations without technical depth. • Shape agentic and conversational experiences that surface AI-powered insights to less-technical customers. • Own shared portal services UX (admin, permissions, authorization, multi-role) that no single team owns today. • Build reusable components and keep UX consistent across portal surfaces. • Ship quickly with the Ordering product and engineering teams using modern AI-assisted tools, and partner with design leadership on cross-product coherence.

• Own forecasting, budgeting, and long-range planning — build and maintain the financial models that drive the annual budget, quarterly and monthly forecasts, and multi-year strategic plans. • Run the planning cycles end to end — partner with department heads to build plans that are both realistic and ambitious, and hold the process together as the single owner of FP&A. • Turn results into insight — analyze actuals against budget and forecast, explain the variances, and translate what happened into what we should do next. • Define and track the metrics that matter — develop KPIs and build clear, trustworthy dashboards and reporting that tell leadership the truth about performance quickly. • Be a true business partner — embed with Sales, Marketing, Product, Engineering, and Operations to support strategic initiatives with financial analysis and a point of view. • Inform the big decisions — prepare board-quality analysis and presentations for the executive team on financial performance, unit economics, and key business drivers. • Support strategic and ad-hoc work — model scenarios for fundraising, new product launches, pricing, and market expansion. • Raise the bar on how finance operates — drive process improvements across the FP&A function to make it faster, more accurate, and more scalable.

• Lead R&D work at Afresh for the development and performance of AI/ML models that power replenishment technology. • Model consumer demand, item-level perishability, and complex multi-echelon supply chains. • Drive fundamental changes to the core system from research through production, writing rigorously tested and scalable code. • Raise the technical bar across the Intelligence team: mentor scientists and engineers, set standards for experimental rigor, and review designs and results. • Push the boundaries of AI capabilities in both products and scientist workflows.

• Set technical direction for core replenishment R&D — define the modeling roadmap across demand forecasting, inventory optimization, and decision-making policy, and align it with product and business strategy. • Model complex problems such as inventory decay, promotions, price elasticity, and inventory uncertainty, and implement solutions to multi-stage and multi-echelon inventory optimization problems. • Drive fundamental changes to our core system from research through production, writing rigorously tested and scalable code. • Lead research and development for new product and business challenges. • Raise the technical bar across the Intelligence team: mentor scientists and engineers, set standards for experimental rigor, and review designs and results. • Push the boundaries of AI capabilities in both products and scientist workflows.

• Set and execute the demand generation strategy across paid media, email, lifecycle, ABM/ABX, content distribution, and integrated campaigns • Make smart investment calls across channels — recommending allocation, prioritizing spend, and partnering with the Head of Marketing to maximize pipeline impact • Build account-driven GTM programs that engage a defined, named-account buyer set — designed for scale through AI-driven personalization, enrichment, and signal-based activation • Flex programs across top, middle, and bottom of funnel as business needs shift • Set the strategy for our event program — trade shows, field activations, and executive dinners — with measurable pipeline outcomes • Manage an event coordinator who runs event logistics; you will own on-site execution • Own our webinar program end-to-end, including content development, speaker coordination, promotion (co-owned with media partner), and redistribution — a meaningful opportunity to shape Afresh's voice across the funnel • Partner with PMM, content, and sales to design distribution plans that get the right content in front of the right buyers at the right moment • Evolve our marketing stack alongside RevOps — bringing your perspective on the AI tools, agents, and workflows that should sit at the center of a modern demand engine • Lead our approach to signal-based automation, lead scoring, and intent-driven campaign activation • Define KPIs and build full-funnel reporting (with RevOps) that connects HubSpot, Salesforce, and our website into a clear view of pipeline performance and ROI • Report on demand performance with clear, synthesized insights and recommendations.

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets. • Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs. • Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets. • Develop tools and frameworks to streamline data integrations and improve scalability. • Define the technical vision for DC data architecture and mentor engineers. • Manage external contractors to ensure the team delivers high-quality, practical solutions. • Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

• Collaborate with engineering teammates to build and ship high-quality applications and services • Work closely with product managers, designers, and users to build engaging user experiences • Provide meaningful feedback on major design choices • Build out analytics and monitoring to understand system behavior • Ensure software quality via automated tests • Design and build reusable and extensible APIs and solutions • Work alongside machine learning specialists to drive new feature development