Role Description - Collect, organize, interpret, and summarize statistical data to contribute to the design and development of Meta products. - Apply expertise in quantitative analysis, data mining, and data presentation to understand user interactions with consumer and business products. - Partner with Product and Engineering teams to solve problems and identify trends and opportunities. - Inform, influence, support, and execute product decisions and launches. - May be assigned projects in various areas including, but not limited to: - Product operations - Exploratory analysis - Product influence - Data infrastructure - Work on problems of moderate scope requiring analysis of various factors. - Exercise judgment within defined procedures and practices to determine appropriate action. - Telecommuting from anywhere in the U.S. is allowed. Qualifications - Bachelor's degree (or foreign equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field. - Completion of a university-level course, research project, internship, or thesis in the following areas: - Performing quantitative analysis including data mining on highly complex data sets. - Data querying language: SQL. - Scripting language: Python. - Statistical or mathematical software including one of the following: R, SAS, or Matlab. - Applied statistics or experimentation, such as A/B testing, in an industry setting. - Machine learning techniques. - ETL (Extract, Transform, Load) processes. - Relational databases. - Large-scale data processing infrastructures using distributed systems. - Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics. Requirements - $222,132/year to $284,900/year + bonus + equity + benefits.

Role Description A pessoa selecionada para essa posição atuará no suporte às atividades analíticas do time, contribuindo para automatização de processos, desenvolvimento de modelos e organização de projetos. - Criar scripts em R ou Python para automatizar tarefas analíticas, gerar resultados de testes e melhorar a eficiência dos fluxos de trabalho. - Apoiar o desenvolvimento de modelos estatísticos e preditivos, seguindo metodologias estabelecidas e trabalhando em conjunto com profissionais mais experientes. - Manter a organização de repositórios e documentação, garantindo consistência, rastreabilidade e estrutura adequada dos materiais técnicos. - Auxiliar em análises e ajustes técnicos relacionados a customizações e estudos conduzidos pela equipe. - Contribuir para a melhoria contínua de workflows, funções e visualizações usadas em processos de modelagem, sempre com foco em performance e qualidade. Benefits - We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. - We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. - Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. - Please read our Candidate Privacy Policy. - We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. Company Description

• You will apply rigorous analytical thinking and modern AI capabilities to design, build, and scale high-impact solutions. • Design, develop, and deploy GenAI-powered internal applications, copilots, and workflow accelerators. • Build reusable AI components, including retrieval pipelines, structured prompting patterns, orchestration workflows, and evaluation harnesses. • Develop and maintain statistical and machine learning models to support automation, optimization, forecasting, and classification use cases. • Design retrieval strategies that connect LLMs to trusted internal knowledge sources, ensuring grounded and reliable outputs. • Implement evaluation and validation frameworks to measure quality, accuracy, and consistency of AI-driven systems. • Partner cross-functionally to identify high-value opportunities for AI enablement across the organization. • Create reusable datasets, feature pipelines, and experimentation frameworks to support iterative development. • Document methodologies, assumptions, and implementation details to ensure transparency and reproducibility. • Uphold high standards for quality, reliability, and responsible AI practices. • Contribute to peer review processes to ensure technical rigor and maintainability.

Role Description We are building our data science capability from the ground up, and this is a rare opportunity to be the founding data scientist embedded within our Growth team. You will own the analytical agenda for growth — from onboarding funnel analysis and top-of-funnel acquisition through to activation, product uptake, and revenue expansion — and for delivering insights that drive meaningful business outcomes. This role sits at the intersection of data engineering, experimentation, and growth strategy. You will work autonomously, partnering closely with growth product managers, engineers, and marketing, and you will have the freedom to build the infrastructure and culture of data-driven decision-making. What You'll Do - Experimentation & A/B Testing - Design, build, and own a robust A/B testing and experimentation framework for the growth function - Define metrics, set up holdout groups, run significance tests, and communicate results with clarity to both technical and non-technical stakeholders - Identify opportunities for rapid iteration and champion a test-and-learn culture across the growth pod - Data Infrastructure & Pipelines - Build and maintain scalable data pipelines and databases that support real-time and near-real-time growth analytics - Develop ETL pipelines (e.g. Python-based) and ensure reliable, clean data flowing into dashboards and models - Collaborate with the Head of Data Engineering to align on tooling, architecture, and best practices - Growth Analytics - Analyse user behaviour across the full funnel — acquisition channels, onboarding, conversion, engagement, and churn - Build models and dashboards that surface actionable insight for the growth and marketing teams - Work closely with AI tools and emerging technologies; bring demonstrable experience of AI-native workflows to the team - Cross-Functional Partnership - Act as the primary data partner for growth PMs, engineers, and marketing stakeholders - Translate complex analyses into clear narratives and recommendations for senior leadership - Over time, help define what a best-in-class data science function looks like and contribute to building it Qualifications - Master’s degree in a quantitative discipline (e.g. Statistics, Computer Science, Mathematics, Engineering) or equivalent practical experience - 4 - 6+ years of experience as a data scientist, ideally within a growth pod or growth-focused team at a scale-up (Series B through pre-IPO) - Hands-on experience building and running A/B testing frameworks from scratch - Strong engineering fundamentals — comfortable building ETL pipelines, data models, and production-quality analytical code (Python preferred) - Experience working with complex, cross-functional data in a fast-paced startup or scale-up environment - AI-native: actively using AI tools in your day-to-day workflow and able to speak to the tangible impact this has had - Comfortable operating autonomously with a builder mindset — there is no established data science function to lean on Preferred Qualifications - Experience at a marketplace business (two-sided platforms with real-time supply/demand dynamics) - Background as a growth analyst or in a growth PM-adjacent role before moving into data science - Prior experience working in Series B–D high-growth companies where you’ve had to build, not just maintain Benefits - Flexible working hours and a vibrant company culture - Remote work - Medical (United Healthcare), Dental, & Vision (Guardian Life) benefit - 401K benefit (Guideline Inc) - Plenty of opportunities for growth and learning - Unlimited holiday allowance - Chance to join and contribute to a company during its exponential expansion phase