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3M

Sr Data Scientist

3M is hiring a Sr Data Scientist in São Paulo, Brazil. Level rates it ; you can apply on 3M.

Level's read on this job

  • Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
  • Tools and skills the posting cites include LangChain, LangGraph and Hugging Face.
  • Level classifies it as a senior role.
  • Level lists 774 other open roles at 3M.

AI in this role

Architect and deploy advanced AI/ML solutions, generative AI models, and agentic workflows at scale.

LangChainLangGraphHugging FaceBedrockPyTorchTensorFlowscikit-learnSageMakerDatabricksAWS BedrockAWS SageMakerAzure ML
ai-agentsml-opscomputer-visionnlpai-safetymachine-learninggenerative-aimlopsllmspython
3M has a long-standing reputation as a company committed to innovation. We provide the freedom to explore and encourage curiosity and creativity. We gain new insight from diverse thinking, and take risks on new ideas. Here, you can apply your talent in bold ways that matter.

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:

  • Work Location: This role follows an on-site working model, requiring the employee to work at least four days a week at the Offices in Sumare, SP, Brasil
  • Travel: May include up to [5%][domestic/international]
  • Relocation: N/A

Supporting Your Well-being

3M offers many programs to help you live your best life – both physically and financially. To ensure competitive pay and benefits, 3M regularly benchmarks with other companies that are comparable in size and scope.

Chat with Max

For assistance with searching through our current job openings or for more information about all things 3M, visit Max, our virtual recruiting assistant on 3M.com/careers.

Learn more about 3M’s creative solutions to the world’s problems at www.3M.com or on Instagram, Facebook, and LinkedIn @3M.

A 3M é um empregador que oferece oportunidades iguais à todos. A 3M não discriminará nenhum candidato baseado em sua raça, cor, idade, religião, gênero, orientação sexual, identidade ou expressão de gênero, nacionalidade ou deficiência.

Safety is a core value at 3M. All employees are expected to contribute to a strong Environmental Health and Safety (EHS) culture by following safety policies, identifying hazards, and engaging in continuous improvement.

Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly.

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How we rate this

Sr Data Scientist at 3M rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsML OpsComputer visionNLPAI SafetyMachine learningGenerative AIMLOps

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$168k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  4. What NLP problem have you worked on, and how did you measure whether it actually worked?
  5. How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

  • List these exact terms on your resume: AI agents, ML Ops, Computer vision, NLP, and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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