Senior Growth Analyst

Vaga não está no LinkedIn

🕒 Julho 8

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $110.000 - $115.000 / ano

⏰ Tempo Integral

🟠 Sênior

📈 Marketing de Crescimento

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

Candidatar-se

Encontrar Vagas Remotas Similares

Configurar Alerta de Email para Novas Vagas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Vida Health

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 2014

🏥 Saúde

🍽️ Alimentos e Bebidas

💼 Consultoria

Healthcare • Food & Beverage • Consulting

A Vida Health é uma empresa comprometida em melhorar os resultados de saúde para várias condições físicas e mentais, incluindo diabetes, obesidade, depressão e hipertensão. Oferecem um cuidado personalizado, liderado por profissionais humanos, combinado com tecnologia digital para gerenciar e tratar essas condições complexas. A Vida Health faz parcerias com empregadores, planos de saúde e consultores para fornecer soluções abrangentes de saúde. Seus serviços incluem bate-papos por vídeo e mensagens de texto com provedores de saúde, e utilizam aprendizado de máquina e dispositivos sincronizados para personalizar o atendimento aos membros. Eles focam em economias de custo significativas e na melhoria dos resultados de saúde para condições cardiometabólicas, garantindo resultados e oferecendo até 100% das taxas de risco tanto para cuidados físicos quanto mentais.

Descrição

• Develop and maintain Braze attributes. This includes defining, building, and validating custom attributes and event structures that enable lifecycle segmentation, targeting, and personalization across communications. • Own marketing attribution analysis, such as measuring how channels, campaigns, and touchpoints contribute to member acquisition and engagement, and translating findings into recommendations on spend, targeting, and channel mix. • Own member engagement analytics, measuring how members engage across their lifecycle, identifying drop-off and opportunity, and delivering insights that inform engagement strategy and operations optimization. • Build and maintain Looker dashboards and reporting that track member engagement, channel effectiveness, and lifecycle outcomes—turning recurring questions into self-serve reporting that member operations and marketing partners can act on. • Partner with Member Operations & Marketing as their analytics counterpart, translating questions about member behavior into analysis and clear, actionable recommendations. • Operate as a proactive analytics partner—anticipating the questions Member Operations and Marketing will ask and surfacing insights before they're requested, rather than waiting on ad-hoc asks. • Apply a working understanding of production SQL and our DBT ETL to reason about how data flows into and interacts with Braze and Looker—validating custom attributes and events, flagging discrepancies, and partnering with data teams to resolve issues. • Design, run, and analyze A/B tests and experiments, translating results into recommendations for member operations and marketing partners. • Other responsibilities as assigned.

🎯 Requisitos

• Bachelors degree at a minimum. • 3-5+ years of experience in member/customer engagement analytics, marketing analytics, or a related quantitative role. • Proven experience building dashboards and reporting in Looker (or a comparable BI tool such as Tableau or Power BI), including working with Explores to enable self-serve analytics for stakeholders. • Working understanding of production SQL, including how DBT ETL models feed and interact with downstream systems like Braze & Looker. • Experience with attribution and revenue recognition analytics. • Proven experience writing SQL to analyze data in BigQuery or a similar relational database. • Fluency with AI-based analytics and coding tools (e.g., Claude, Claude Code) to accelerate query writing, analysis, and reporting, having used them to scale output while validating results for accuracy. • Comfortable designing and interpreting experiments and A/B tests. • Strong communication skills—able to translate analysis into clear recommendations for non-technical partners.