• Support the Data Science team in the following activities: • Interpret and translate business requirements into statistical modeling solutions • Organize, structure, and document projects from start to finish • Develop statistical models tailored to each need • Deepen business knowledge to anticipate the best use of proposed solutions • Create monitoring reports for the statistical models developed • Communicate and present results to both technical teams and business stakeholders

• Own the analytical strategy for the end-to-end marketing funnel, from marketable lives to lead generation to omni-channel engagement strategy to visit completion and re-engagement. This includes our call center function (outbound rep allocation, inbound referral scheduling, ZCC data) and member lifecycle (Customer.io journey performance, reactivation, and initial visit completion optimization). • Own the product analytics domain: onboarding funnel, sign-up conversion, in-app engagement, and the member experience through completed first appointment. Partner with the top-of-funnel product team as their embedded analytical lead, attending product cadences and co-owning the product analytics roadmap. • Serve as the executive-facing owner of the marketing and product performance narrative: explaining why marketable lives, funnel conversion, and initial visit completion moved, what levers drove the result, and what to double down on. • Design and lead Foodsmart's experimentation program across both marketing and product, including test design, causal inference methods, readout discipline, and the intake process for stakeholder-driven test ideas. Own the StatSig implementation and serve as the internal expert on experiment instrumentation, StatSig configuration, and results interpretation. • Own and evolve our attribution framework, including scheduling episode attribution, multi-touch attribution, and media mix modeling as Foodsmart's channel portfolio grows. • Partner with Growth Marketing leadership as the embedded analytical lead: attending marketing cadences, co-owning the analytics roadmap, and driving insight into action. • Own and evolve the dbt data models for the marketing and product domains — from raw source modeling through mart-layer metrics — ensuring data quality, test coverage, documentation, and a semantic layer that makes self-service trustworthy. This is a core craft expectation of this role, not a secondary responsibility. • Engineer context into our semantic layer and BI environment (Omni) so that stakeholders and AI agents can reliably self-serve answers across the marketing and product funnel. You treat context engineering — writing descriptions, defining metrics, curating what's exposed — as a first-class part of your job. • Drive the narrative, not just the numbers — translate findings into clear, actionable recommendations for executive and marketing leadership audiences. • Raise the bar for the analytics team on the craft areas central to this role — experimentation design, dbt modeling patterns, and context engineering. You don't manage anyone, but you operate as a technical leader: establishing best practices, reviewing work, and making the team around you better.

Role Description Estamos em busca de um(a) Cientista de Dados – IA Generativa e Azure para integrar nosso time e atuar de forma estratégica no desenvolvimento de soluções inteligentes baseadas em Inteligência Artificial. Esse profissional terá papel fundamental na criação, integração e evolução de aplicações com IA generativa, Large Language Models (LLMs) e serviços de Azure AI, atuando desde a concepção até a disponibilização dos modelos em produção. A atuação será end-to-end, colaborando diretamente com times de engenharia, dados e produto para gerar valor real ao negócio por meio de dados e IA. - Desenvolver e integrar soluções de Inteligência Artificial utilizando Azure AI Foundry, Azure OpenAI, Cognitive Services e Azure Machine Learning. - Criar aplicações baseadas em IA generativa e Large Language Models (LLMs) para resolver problemas de negócio e gerar valor a partir de dados. - Desenvolver pipelines de inferência e APIs para disponibilização de modelos de IA em produção. - Trabalhar com engenharia de prompts, RAG (Retrieval-Augmented Generation) e embeddings para aplicações com LLMs. - Criar, treinar e ajustar modelos de Machine Learning e NLP, quando necessário. - Implementar fine-tuning e customização de modelos de IA conforme necessidades específicas do negócio. - Projetar soluções escaláveis utilizando arquitetura serverless e microsserviços no Azure. - Aplicar práticas de MLOps para automação, monitoramento e versionamento de modelos. - Atuar de forma colaborativa com times de engenharia, dados e produto no desenvolvimento de aplicações inteligentes. - Acompanhar evoluções tecnológicas em IA generativa, LLMs e serviços Azure AI. Qualifications - Experiência no desenvolvimento de aplicações com IA generativa e modelos pré-treinados (LLMs). - Experiência com Azure AI Foundry, Azure OpenAI, Azure Machine Learning ou serviços similares. - Domínio de Python para desenvolvimento de soluções de IA. - Experiência com bibliotecas e frameworks de Machine Learning (Scikit-learn, PyTorch, TensorFlow ou similares). - Experiência em integração de APIs e desenvolvimento backend para aplicações de IA. - Conhecimento em RAG, embeddings, vector databases ou arquiteturas baseadas em LLMs. - Experiência com MLOps, CI/CD e deploy de modelos em produção. - Experiência com bancos de dados SQL e NoSQL. - Familiaridade com Git, Azure DevOps e pipelines de CI/CD. Requirements - Capacidade de atuar de forma colaborativa com equipes multidisciplinares. - Pensamento analítico, autonomia e foco em resolução de problemas. - Boa comunicação para interação com áreas técnicas e de negócio. - Inglês avançado para leitura, escrita e conversação. Differentials - Experiência avançada com LLMs e IA generativa em produção. - Experiência com LangChain, Semantic Kernel, LlamaIndex ou frameworks de orquestração de LLMs. - Experiência com vector databases (Pinecone, Qdrant, Weaviate, pgvector, entre outros). - Experiência com arquitetura de aplicações de IA em cloud (Azure, AWS ou GCP). - Certificações Azure AI Engineer Associate ou Azure Data Scientist Associate. Benefits - Plano de Saúde SulAmerica - Plano Odontológico SulAmerica - Auxílio Home Office - Grupos de Estudos - Suporte para Certificações Microsoft - Seguro de Vida - Gympass

Title: Senior Epidemiologist, Real-World Evidence (FSP Sponsor Dedicated) Location: - US Remote - Durham, North Carolina, United States of America - Minneapolis, MN - Boston, MA - Wayne, PA, United States of America - New York, NY - San Francisco, CA Job Description: Join IQVIA's Sponsor-Dedicated FSP team and help advance healthcare through real-world evidence. We bring together scientific expertise and real-world data to help sponsors make decisions and accelerate evidence generation to improve patient outcomes. In this role, you'll work closely with one sponsor, gaining deep knowledge of their therapies while leveraging IQVIA's global expertise. Overview: IQVIA is seeking an accomplished epidemiology leader to drive the design and execution of innovative real-world evidence (RWE) strategies for a leading sponsor organization. This senior role combines scientific rigor with strategic influence, enabling you to shape high-impact observational research that informs clinical development, regulatory decisions, and market access. Responsibilities: Study Lead: Lead execution of studies to generate actionable RWE within agreed timelines, budgets, and quality standards. Focus areas include but not limited to: - External comparators - Natural history of disease - Treatment patterns and switching - Comparative safety/effectiveness Epidemiology Leadership: Design and drive development of study protocols, statistical analysis plans, and study reports addressing priority methodological questions. Data Strategy: Conduct feasibility and assessment of fit-for-purpose real-world data (RWD) sources (claims, EHR, registries) to enable timely execution of RWE initiatives. RWD expertise: Construct cohorts, validate key variables, and guide implementation of descriptive and comparative analyses using RWD for complex research questions. Stakeholder Engagement: Build strong partnerships with internal teams, external vendors, and sponsor stakeholders to ensure alignment and delivery of strategic objectives. What's in it for you? - Be part of a forward-thinking team that helps shape the next generation of evidence-based healthcare. - Work hand-in-hand with one leading sponsor, gaining deep expertise in their therapies. - Access IQVIA's global network who supports your growth This is your chance to make an impact, while building a career that matters. This is a remote role. Candidates must be based in the US. IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com IQVIA is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by applicable law. https://jobs.iqvia.com/eoe IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism. The potential base pay range for this role, when annualized, is $110,500.00 - $276,100.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.