Senior Head of Data & AI
New
BrazilFull-TimeManager
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 4–5+ years of experience leading Data Science, Machine Learning, or AI teams in a managerial capacity.
- Required Skills
- LeadershipPythonArtificial IntelligenceMachine LearningData scienceA/B testingLangChain
Requirements
- 4–5+ years of experience leading Data Science, Machine Learning, or AI teams in a managerial capacity.
- Strong expertise in machine learning techniques, including regression, classification, clustering, neural networks, model evaluation, and explainability.
- Solid background in probability, statistics, experimental design, causal inference, optimization, and A/B testing methodologies.
- Hands-on experience building, deploying, and maintaining production-grade machine learning systems.
- Advanced proficiency in Python and modern software engineering best practices.
- Proven ability to collaborate with cross-functional stakeholders and communicate technical concepts to both technical and business audiences.
- Advanced English communication skills.
- Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, LangChain, LangGraph, or similar frameworks is highly desirable.
- Postgraduate qualifications (MSc or PhD) are considered an asset.
- NLP and Deep Learning experience are considered assets.
- Startup experience is considered an asset.
Responsibilities
- Lead and mentor a team of Data Scientists and Machine Learning Engineers, fostering technical excellence, collaboration, and continuous professional growth.
- Define and execute the organization's Data & AI strategy while aligning technical initiatives with business priorities and product roadmaps.
- Serve as a senior technical authority by architecting, developing, and deploying scalable machine learning solutions into production when required.
- Partner with Product Managers and senior stakeholders to translate business challenges into data-driven solutions and strategic initiatives.
- Guide the design and execution of experiments, statistical analyses, and model development using both structured and unstructured data.
- Establish team goals, monitor performance, and cultivate a high-performance engineering culture focused on innovation and measurable outcomes.
- Champion best practices in machine learning, software engineering, experimentation, and AI adoption across the organization.
- Promote a data-driven mindset by advocating for the value of analytics and artificial intelligence throughout the business.
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