• 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.

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency • This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis • You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time • Your primary metric is ROAS • Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact • Deliver buying models that maintain positive ROAS and quality • Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth • Establish trusted, direct partnership with vertical business stakeholders • Produce trusted output: validated, documented, low correction burden • Identify and leverage net-new modeling opportunities the business has not flagged

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency • Collaborate directly with stakeholders, building and validating models, and ensuring effective deployment and performance analysis • Start focusing on Insurance and Advertiser Quality, with future scope expansions • Drive lead quality improvements across various brand portfolios leading to revenue growth