3M Brasil (Workday)
BR, São Paulo, Sumare
Sr Data Scientist
Full time
PRIMEIRA CAPTURA
17/08/2026
EarlyCV
Job Description:
Collaborate with innovative 3Mers around the world
As a Senior Data Scientist, you will be a key technical leader within the Global Analytics & Insights (A&I) organization, driving the design and delivery of advanced AI/ML solutions that create strategic business value at scale. You will combine deep technical expertise in generative AI, AI agents, and machine learning with strong business proficiency, leading high-impact initiatives and influencing the Innovation direction of the organization.
This role is ideal for experienced data science professionals who are ready to own complex Innovation solution architectures, mentor peers, and bridge the gap between cutting-edge AI capabilities and real-world enterprise applications across a global, innovation-driven environment.
The Impact You Will Make in This Role
Advanced AI & Machine Learning Leadership
Architect, develop, and deploy sophisticated AI/ML solutions across multiple domains, including predictive models, generative AI technologies, agentic solutions, NLP pipelines, and computer vision systems.
Lead the full Innovation lifecycle - from opportunity identification and discovery through development, deployment, and ongoing performance management.
Define and own AI/ML model design and development approaches, ensuring technical excellence, scalability, and alignment with 3M standards.
Drive the adoption and integration of large language models (LLMs), generative AI frameworks, and AI agent architectures to solve complex business problems.
Establish and enforce model validation, testing criteria, and governance standards across the team.
Champion responsible for AI/ML principles, including model explainability, fairness, cost management, bias mitigation, and compliance with ethical standards.
Cloud & Data Platform Expertise
Lead the development and optimization of AI/ML pipelines on/with AWS Bedrock, AWS Agent Core, AWS SageMaker, Azure ML, and Databricks, ensuring production-grade reliability and performance.
Partner with data engineering teams to define data architecture requirements, pipeline standards, and quality frameworks that support advanced analytics and AI at scale.
Drive MLOps best practices, including CI/CD for ML, model monitoring, retraining strategies, and deployment automation.
Strategic Influence & Stakeholder Engagement
Engage proactively with 3M stakeholders, A&I Pillar Leads, and IT COE partners to identify high-value AI opportunities and translate them into structured, impactful solution roadmaps.
Influence AI technology stack recommendations and contribute to the broader A&I innovation agenda.
Lead stakeholder engagement throughout solution design, testing, validation, and adoption phases, ensuring solutions are embedded and delivering value.
Provide technical mentorship and guidance to mid-level Data Scientists and AI Specialists, elevating team capabilities and fostering a culture of technical excellence.
Communicate complex AI/ML concepts and model outcomes clearly and persuasively to senior technical and non-technical stakeholders.
Documentation & Governance
Own comprehensive documentation of model architecture, data lineage, performance metrics, and governance artifacts for all AI solutions developed.
Apply 3M development standards and responsible AI frameworks consistently across all deliverables.
Proactively identify and mitigate risks related to model bias, data drift, data quality, and solution reliability.
Your Skills and Expertise
Required Qualifications
Experience: Minimum of 5–8 years of hands-on experience in Data Science, Machine Learning, or AI roles, with a strong track record of delivering AI/ML solutions in enterprise production environments.
Education: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, Statistics, or a related field.
Technical Skills:
Advanced proficiency in Python with practical experience building scalable data science and AI solutions. The candidate should be able to use Python for data analysis, machine learning and AI development, API creation, workflow automation, and the design of agentic architectures that integrate tools, models, and enterprise systems.
Hands-on experience with LLMs, Generative AI tools and Agentic framework (e.g., Strands, LangChain, LangGraph, Hugging Face).
Deep expertise with ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn, and equivalent tools.
Advanced hands-on experience with cloud AI/ML platforms: AWS Bedrock, AWS Agent Core, AWS SageMaker, and Azure ML.
Proven experience with LLMs, Generative AI frameworks (e.g., LangChain, LangGraph, Hugging Face), and AI agent architectures.
Strong command of MLOps practices: model versioning, CI/CD pipelines, monitoring, and retraining strategies.
Solid understanding of data engineering principles, ETL/ELT pipelines, and data quality frameworks.
AI Focus Areas: Demonstrated expertise across multiple domains: Predictive Modeling & Forecasting, NLP / LLMs, Agentic Architecture, Computer Vision, and MLOps / Model Productionization.
Communication: Proficiency in English (written and spoken); proven ability to present AI strategies and outcomes to senior leadership.
Additional Qualifications (Nice to Have)
Knowledge of model explainability and responsible AI tools (e.g., SHAP, LIME, Fairlearn).
Familiarity with data visualization platforms (e.g., Matplotlib, Seaborn, Power BI) and storytelling with data.
Experience in solution architecture decisions within enterprise AI/ML contexts.
Background in software engineering best practices: version control (Git/GitHub), code review, and modular development.
Proficiency in Spanish.
Key Behavioral Competencies (Soft Skills)
Strong technical leadership and ability to influence without authority across cross-functional teams.
Excellent structured thinking, with the ability to break down ambiguous problems into actionable Innovation solutions.
Highly effective communicator across technical and executive audiences in multicultural and global environments.
Proactive, self-directed, and comfortable navigating complexity and ambiguity in a fast-evolving AI landscape.
Collaborative mentor who elevates team performance and fosters a culture of innovation and continuous learning.
Work location:
Supporting Your Well-being
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