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The Principal Product Manager will lead the customer account platform and AI-powered identity management, focusing on enhancing user experiences and security through automation and innovation.

Lead and automate weekly/monthly financial modeling and P&L reporting, partner with cross-functional teams to drive budgeting, forecasting, variance and scenario analyses, surface risks and opportunities, and deliver actionable insights to senior leadership to support strategic decisions.

Provide frontline HR support across day and night warehouse shifts: manage timecards, onboarding/offboarding, maintain HRIS records, coordinate scheduling and attendance, assist with audits/investigations, and support training, engagement, and recognition efforts for hourly associates.

Partner with corporate and warehouse leaders to develop HR strategy, workforce planning, performance management, compensation, succession planning, employee relations, compliance, and talent acquisition. Drive engagement, retention, and organizational design while supporting onboarding and coaching frontline managers in a shift-based, 24/7 warehouse environment.

Manage evening (PM) training operations: lead onboarding and trainer meetings, audit trainer delivery and SOP adherence, coach trainers, track new-hire progress and cross-training, maintain Google Sheets dashboards and reporting, identify training gaps, and support curriculum and change management to ensure consistent training quality and compliance.

Design, build, and own Quince's end-to-end ML platform (training, serving, feature pipelines, monitoring). Create developer-facing MLOps tooling, select core components, optimize GPU and cloud costs, ensure scalable, reliable production deployments, lead RCAs, and mentor engineering teams to raise platform and operational standards.

Provide brand-aligned customer support across chat, email, phone, and social channels; own interactions end-to-end; resolve issues empathetically; use service platforms and AI-assisted tools; surface recurring friction and product feedback; become a product expert; meet response time, accuracy, and productivity targets.

Lead end-to-end supply chain planning science: own forecasting tournaments, inventory placement optimization, vendor performance systems, and raw-material signals. Define methodology, production models, and iteration loops; drive AI-native workflows (LLM-aided EDA, agentic feature engineering), partner with planning operators and engineering, and mentor junior scientists to raise methodological standards and deliver measurable business impact.

Lead end-to-end supply chain planning and forecasting modeling: demand forecasting across geographies, forecasting tournaments, inventory placement optimization, vendor performance modeling, and raw-material signal generation. Collaborate with leadership and engineering to productionize models and apply AI-native techniques (LLM-aided EDA, agentic feature engineering, AI-augmented experimentation).

Lead sourcing for sweater categories: identify, vet, pitch, onboard and scale vendors; manage supplier performance and compliance; optimize pricing, costs and replenishment; build contingency plans and cross-functional collaboration to improve quality, speed, and margins.