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3M

Diversified technology manufacturer of adhesives, PPE.

Senior Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSumaré, State of São Paulo, BrazilNo salary listed

About the Job

Requirements

  • A 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.
  • A bachelor's or master's degree in Computer Science, Data Science, Mathematics, Engineering, Statistics, or a related field.
  • Advanced proficiency in Python for data analysis, machine learning and AI development, API creation, workflow automation, and designing agentic architectures that integrate tools, models, and enterprise systems.
  • Hands-on experience with large language models, generative AI tools, and agentic frameworks such as Strands, LangChain, LangGraph, or Hugging Face.
  • Deep expertise with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and Scikit-learn, or equivalent tools.
  • Advanced hands-on experience with cloud AI/ML platforms including AWS Bedrock, AWS Agent Core, AWS SageMaker, and Azure ML.
  • Proven experience with large language models, generative AI frameworks such as LangChain, LangGraph, or Hugging Face, and AI agent architectures.
  • Strong command of MLOps practices, including model versioning, continuous integration and continuous delivery pipelines, monitoring, and retraining strategies.
  • A solid understanding of data engineering principles, ETL/ELT pipelines, and data quality frameworks.
  • Demonstrated expertise across multiple areas including predictive modeling and forecasting, natural language processing and large language models, agentic architecture, computer vision, and MLOps/model productionization.
  • Proficiency in English, written and spoken, and the ability to present AI strategies and outcomes to senior leadership.
  • Strong technical leadership and the ability to influence across cross-functional teams without authority.
  • Structured thinking and the ability to break down ambiguous problems into actionable solutions.
  • Effective communication across technical and executive audiences in multicultural and global environments.
  • A proactive, self-directed approach and comfort navigating complexity and ambiguity in a fast-evolving AI landscape.
  • A collaborative mentoring approach that elevates team performance and fosters continuous learning.

Responsibilities

  • Architect, develop, and deploy advanced AI/ML solutions across domains including predictive models, generative AI technologies, agentic solutions, natural language processing pipelines, and computer vision systems.
  • Lead the 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 company standards.
  • Drive adoption and integration of large language models, generative AI frameworks, and AI agent architectures to solve complex business problems.
  • Establish and enforce model validation and testing criteria, and governance standards across the team.
  • Champion responsible AI principles, including model explainability, fairness, cost management, bias mitigation, and compliance with ethical standards.
  • Lead the development and optimization of AI/ML pipelines using 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 continuous integration and delivery for machine learning, model monitoring, retraining strategies, and deployment automation.
  • Engage with stakeholders, A&I Pillar Leads, and IT COE partners to identify high-value AI opportunities and translate them into structured 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 to ensure solutions are embedded and deliver value.
  • Provide technical mentorship and guidance to mid-level Data Scientists and AI Specialists, elevating team capabilities and technical excellence.
  • Communicate AI/ML concepts and model outcomes to senior technical and non-technical stakeholders.
  • Own documentation of model architecture, data lineage, performance metrics, and governance artifacts for AI solutions.
  • Apply development standards and responsible AI frameworks across deliverables.
  • Identify and mitigate risks related to model bias, data drift, data quality, and solution reliability.
  • Work on-site at the Sumaré, São Paulo office at least four days per week; the role may include up to 5% domestic or international travel.
  • Follow safety policies, identify hazards, and engage in continuous improvement as part of the Environmental Health and Safety culture.

Desired Qualifications

  • Knowledge of model explainability and responsible AI tools such as SHAP, LIME, or Fairlearn.
  • Familiarity with data visualization platforms such as Matplotlib, Seaborn, or Power BI, and storytelling with data.
  • Experience making solution architecture decisions within enterprise AI/ML contexts.
  • A background in software engineering best practices, including version control with Git/GitHub, code review, and modular development.
  • Proficiency in Spanish.

About the Company

3M

Diversified technology manufacturer of adhesives, PPE.

3M is a diversified technology and manufacturing company that sells products in adhesives, tapes, abrasives, personal protective equipment, healthcare, automotive, and household goods. Its products work by applying materials science to solve tasks such as bonding, finishing, protecting people, enabling diagnostics, and everyday applications. It differentiates itself through a large patent portfolio, extensive R&D, collaborations, and a broad multi-market footprint, plus a long-running sustainability program. Its goal is to deliver reliable solutions that address real-world needs while advancing environmental and social responsibility and creating value across its markets.

Company size
10,001+
Company stage
IPO
Headquarters
St Paul, MN
Founded
1902

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