Senior Data Scientist

As a Senior Data Scientist at 3M, 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.

The Impact You Will Make in This Role

• 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

• 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. + 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.

• 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.