Senior Applied Scientist

Senior Applied Scientist – AI/ML Customer Science (Remote – Brazil) Location: 100% Remote (Brazil) Employment Type: PJ – Long term About the Role We 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 On You will build models and platforms that create impact across areas such as: Sales prioritization and expected value modeling Marketing targeting and uplift modeling Multi-touch attribution and incrementality measurement Customer lifecycle modeling (conversion, retention, churn, LTV) Outreach optimization and personalization systems Responsibilities Research, design, and develop machine learning, statistical, and causal models for Marketing and Sales use cases including: Propensity and expected value modeling Uplift and treatment effect estimation Attribution and marketing measurement Forecasting, optimization, and prioritization systems Translate business growth problems into clear objectives, loss functions, and evaluation frameworks Design feature representations capturing customer behavior, engagement, and lifecycle dynamics Design 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, monitoring Develop scalable ML services integrated into business workflows (CRM, marketing platforms, internal tools) Partner closely with Product, Engineering, Marketing, Sales, and Data teams Influence technical direction and roadmap prioritization based on business impact Clearly communicate insights and model behavior to technical and non-technical stakeholders Mentor junior scientists and engineers and help establish best practices Contribute to long-term data science strategy, platforms, and innovation Minimum Qualifications 5+ years of industry experience in applied Machine Learning Master's degree or PhD in Computer Science, Machine Learning, Statistics, Operations Research, or related field 3+ years of experience building, deploying, and managing ML models in production at scale Strong knowledge of ML best practices (feature engineering, experimentation, pipelines, model evaluation) Experience with modern ML techniques including gradient boosting, deep learning, transformers, and optimization Experience in Computer Vision (Causal Inference experience is a strong plus) Proficiency in Python and SQL Hands-on experience with ML frameworks: PyTorch, TensorFlow, Keras, Scikit-learn Strong data engineering skills with large-scale datasets Experience with big data tools such as Apache Beam, Kafka, Spark Experience with cloud platforms (AWS, GCP, or Azure) Preferred Qualifications PhD in CS, ML, AI, Statistics, Operations Research, or related field Experience applying ML in retail or commercial business contexts Familiarity with MLOps tools and production pipelines Strong leadership and mentoring experience Impact-driven mindset with a focus on delivering high-quality, scalable solutions