Top Tech Jobs & Startup Jobs in NYC, NY

Own and build Confido's ML platform: design and operate end-to-end ML pipelines, infrastructure-as-code and CI/CD, optimize training/inference and agent workloads for latency/cost/throughput, integrate model data flows with data engineering, and ensure reliability, observability, security, and production model quality with online evals and human-in-the-loop review.

Lead end-to-end customer implementations for demand and supply planning modules. Responsibilities include data mapping and validation, platform configuration, forecasting and inventory workflow setup, implementation timeline management, user training, and issue resolution. The role translates CPG planning processes into Confido and communicates implementation insights to product and engineering teams.

Lead strategic finance, FP&A, and reporting initiatives; build financial models for pricing, market sizing, and unit economics; partner with Revenue on forecasting and ROI analysis; create investor and board materials; run ad-hoc strategic analyses and collaborate with data/engineering to build financial insights infrastructure.

Lead end-to-end customer implementations for demand and supply planning modules, including data mapping, configuration, validation, workflow setup, and go-live. Partner with customer planning teams to configure forecasting, inventory, replenishment, and production processes. Validate data, manage timelines and action items, train users, resolve implementation issues, and share customer feedback with product and engineering teams.

Develop go-to-market strategy and sales enablement for strategic deals. Research accounts, markets, competitors, and customer workflows; create executive presentations, proposals, product narratives, competitive positioning, ROI analyses, and business cases. Partner with sales, product, and leadership teams on product commercialization and scalable GTM frameworks. The role requires strong analytical, financial, communication, and presentation skills, with five-day-a-week work from the New York City headquarters.

Own full-cycle recruiting across technical and non-technical functions, including sourcing, candidate evaluation, hiring-manager calibration, stakeholder accountability, and closing. Manage a high requisition load while maintaining quality and candidate experience, partnering with hiring managers and a dedicated sourcer. Recruit across GTM, BizOps, Marketing, Product, Design, and Engineering as company hiring needs evolve.

Lead Confido’s creative brand direction as its first creative brand hire. Translate the new identity into a distinctive, consistent system across the website, campaigns, decks, advertising, events, video, and product experiences. Develop compelling stories from customer outcomes and CPG operations, oversee creative production, and build a network of specialist talent. Partner with founders, marketing, and product design while owning creative standards, vendors, budgets, and execution from concept through production.

Lead and grow Confido’s data engineering team, initially managing an analytics engineer while remaining hands-on with SQL, data models, pipelines, and code reviews. Own warehouse architecture, orchestration, tooling, data standards, monitoring, and metric definitions. Hire and develop engineers, prioritize the team’s roadmap, collaborate across departments, and improve data reliability, documentation, and reporting across the company.

Build Confido’s analytics layer by creating dashboards, reports, metrics, and analytical tools for internal and customer users. Analyze large financial and operational datasets with advanced SQL, identify trends and inefficiencies, and translate findings into actionable recommendations. Partner with product, engineering, customers, and other stakeholders to improve data models, deliver analytical projects, and support decision-making across retail, finance, and operations.

Lead Confido’s data science function for Revenue Growth Management, developing pricing, promotion, forecasting, causal inference, and optimization models. Translate predictions into actionable recommendations under budget, margin, and retailer constraints. Partner with AI/ML engineers on productionization, evaluation, backtesting, and monitoring. Hire and mentor a team of data scientists while setting technical direction with company leadership.