5 дней назад
Analytics Manager (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Analytics Manager (AI): Leading analytics engineering, business intelligence, and AI-enabled analytics to build reliable data foundations and improve patient outcomes with an accent on team leadership, data modeling, and cross-functional decision support. Focus on defining the analytics roadmap, optimizing scalable pipelines, and solving ambiguous business questions across operations, marketing, supply, and demand.
Location: New York, NY; hybrid schedule with the Data team in the office 2–3 days per week
Company
is an AI-native digital health system delivering dietitian-led metabolic healthcare through registered dietitians, physicians, medications, lab testing, and AI agents.
What you will do
- Lead, develop, plan, and prioritize the work of a team of Analytics Engineers.
- Define and deliver the analytics roadmap across data modeling, business intelligence, and AI-enabled analytics.
- Lead analyses of ambiguous business problems and provide high-impact insights to leadership.
- Partner with Engineering to validate and optimize data pipelines and maintain a reliable single source of truth.
- Establish technical standards, documentation practices, and evidence-based decision-making across the business.
- Collaborate with Operations, Engineering, Product, marketing, and supply-and-demand teams.
Requirements
- 5+ years of relevant experience owning analytics end to end in a fast-paced, high-growth company.
- 2+ years of leadership experience, including setting and driving technical vision.
- Deep analytics engineering expertise with clean, performant SQL, data modeling, ETL, and data infrastructure.
- Hands-on experience with dbt and Fivetran.
- Ability to structure ambiguous problems into thoughtful roadmaps and translate complex data into actionable insights.
- Interest in working with a New York City-based team and attending the office 2–3 days per week.
Culture & Benefits
- High-accountability environment focused on solving difficult, meaningful healthcare problems.
- Culture of candid feedback, resilience, ownership, and low ego.
- Opportunity to improve patient outcomes and build analytics capabilities at scale.
- Collaboration with Operations, Engineering, Product, and company leadership.
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