Senior Applied Scientist – AI/ML Customer Science (Remote – Brazil)Location: 100% Remote (Brazil)Employment Type: PJ – Long termAbout the RoleWe are looking for a Senior Applied Scientist to design, develop, and deploy advanced machine learning, causal inference, and optimization systems that drive Marketing and Sales decision-making. In this role, you will transform complex customer behavior and business growth challenges into measurable objectives and scalable ML solutions across acquisition, conversion, retention, and revenue optimization. You will work at the intersection of machine learning, experimentation, causal inference, and business strategy in a fast-paced, collaborative, and entrepreneurial environment.What You’ll Work OnYou will build models and platforms that create impact across areas such as:Sales prioritization and expected value modelingMarketing targeting and uplift modelingMulti-touch attribution and incrementality measurementCustomer lifecycle modeling (conversion, retention, churn, LTV)Outreach optimization and personalization systemsResponsibilitiesResearch, design, and develop machine learning, statistical, and causal models for Marketing and Sales use cases including:Propensity and expected value modelingUplift and treatment effect estimationAttribution and marketing measurementForecasting, optimization, and prioritization systemsTranslate business growth problems into clear objectives, loss functions, and evaluation frameworksDesign feature representations capturing customer behavior, engagement, and lifecycle dynamicsDesign and analyze experiments (A/B tests, geo tests, incrementality tests, diff-in-diff, causal impact)Build and maintain robust evaluation frameworks aligned with business outcomes (ROI, CAC, conversion, retention, LTV)Own the end-to-end ML lifecycle: data ingestion, feature engineering, training, deployment, monitoringDevelop scalable ML services integrated into business workflows (CRM, marketing platforms, internal tools)Partner closely with Product, Engineering, Marketing, Sales, and Data teamsInfluence technical direction and roadmap prioritization based on business impactClearly communicate insights and model behavior to technical and non-technical stakeholdersMentor junior scientists and engineers and help establish best practicesContribute to long-term data science strategy, platforms, and innovationMinimum Qualifications5+ years of industry experience in applied Machine LearningMaster’s degree or PhD in Computer Science, Machine Learning, Statistics, Operations Research, or related field3+ years of experience building, deploying, and managing ML models in production at scaleStrong knowledge of ML best practices (feature engineering, experimentation, pipelines, model evaluation)Experience with modern ML techniques including gradient boosting, deep learning, transformers, and optimizationExperience in Computer Vision (Causal Inference experience is a strong plus)Proficiency in Python and SQLHands-on experience with ML frameworks: PyTorch, TensorFlow, Keras, Scikit-learnStrong data engineering skills with large-scale datasetsExperience with big data tools such as Apache Beam, Kafka, SparkExperience with cloud platforms (AWS, GCP, or Azure)Preferred QualificationsPhD in CS, ML, AI, Statistics, Operations Research, or related fieldExperience applying ML in retail or commercial business contextsFamiliarity with MLOps tools and production pipelinesStrong leadership and mentoring experienceImpact-driven mindset with a focus on delivering high-quality, scalable solutions