Data Scientist

Job Summary

Amana is seeking a visionary Data Scientist to lead enterprise-grade AI/ML initiatives that transform how we operate and make decisions. Operating at the intersection of advanced machine learning, ERP-integrated analytics, and data governance, this role plays a foundational part in Amana's digital transformation. As a senior member of the Data Science Center of Excellence, you will drive high-impact projects, mentor talent, and work closely with cross-functional stakeholders to turn data into actionable intelligence.

This role is ideal for a technically proficient leader who thrives in a hands-on yet strategic environment and has a strong record of delivering value through production-grade AI systems.

Why This Role Matters

Amana operates across capital-intensive sectors where operational efficiency, risk prediction, and real-time decision-making are business-critical. AI is a strategic enabler across these domainsfrom optimizing costs and improving resource utilization to building intelligent automation in our ERP ecosystem.

You will be at the forefront of this transformation, designing and deploying scalable AI systems that are ethical, explainable, and aligned with enterprise priorities.

Core Responsibilities

AI/ML Solution Development & Integration

• Design, train, and deploy end-to-end ML pipelines using Azure ML, Databricks, and MLOps frameworks.
• Build production-grade models in forecasting, optimization, NLP, and recommendation systems.
• Integrate AI models with ERP systems for real-time insights and operational triggers.
• Lead design and deployment of LLM-powered assistants and Agentic AI solutions.
• Implement model monitoring, explainability, bias mitigation, and lifecycle management practices.

Strategic Leadership & Mentorship

• Translate business challenges into data science opportunities through close engagement with business, IT, and product stakeholders.
• Mentor and guide junior data scientists, fostering a culture of experimentation and continuous learning.
• Represent the Data Science team in innovation councils, steering committees, and cross-functional projects.
• Contribute to the enterprise AI roadmap in alignment with digital transformation objectives.

Data Governance & Trustworthy AI

• Partner with the Data Governance Office to embed data stewardship, lineage tracking, and cataloging into AI workflows.
• Ensure all models comply with regulatory, ethical, and internal policies on data privacy, fairness, and auditability.
• Lead the development of data validation and anomaly detection systems to maintain data integrity.

Intelligent Automation & System Integration

• Collaborate with IT and solution architects to ensure scalable, secure, and maintainable deployment of AI models.
• Build reusable APIs and components to integrate models with business systems like ERP, CRM, and dashboards.
• Design automation flows using Power Automate, UIPath, and Azure Logic Apps to augment AI output with actionable triggers.

Project & Vendor Oversight

• Lead AI project delivery with clear milestones, success metrics, and stakeholder alignment.
• Manage relationships with external AI vendors, consultants, and data providers to ensure solution quality and business fit.
• Drive adoption of AI solutions through structured change management and user enablement programs.

Required Qualifications

• 5+ years of experience in applied data science, including deploying models with tangible business impact.
• Proven ability to deliver ML solutions in production using Python, scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with Microsoft Azure ML, Databricks, Delta Lake, Synapse, and Azure SQL.
• Strong grasp of data engineering concepts and data lakehouse architectures.
• Working knowledge of ERP systems, including data structures and integration patterns.
• Practical understanding of MLOps, model lifecycle, and monitoring techniques.
• Familiarity with Microsoft Purview and enterprise data governance frameworks.
• Excellent communication and stakeholder management skills across technical and business domains.

Preferred Qualifications

• Experience with LLM frameworks such as LangChain, Semantic Kernel, or OpenAI APIs.
• Exposure to AutoML, causal inference, reinforcement learning, or generative AI.
• Proficiency with BI tools (e.g., Power BI, Azure Analysis Services).
• Understanding of federated data governance, data mesh, or data fabric concepts.
• Industry experience in highly regulated environments (e.g., energy, healthcare, finance) is a plus.

Certifications

• Microsoft Certified: Azure Data Scientist Associate (DP-100)
• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• Certified Data Management Professional (CDMP)
• RPA certifications (UIPath, Power Automate)
• Data Governance certifications (e.g., DCAM, Collibra, DAMA)