Senior Data Scientist

Graybar • Clayton, MO

2d • Hybrid

About The Position

Make a difference. As a Senior Data Scientist, you will build and operationalize internal AI and machine learning capabilities that automate sales, customer service, and administrative workflows to applied ML models that drive the business. You will establish practices, platforms, and models that will define the Company AI at scale. You will also work across Graybar’s AI portfolio designing and deploying intelligent agents, building retrieval-augmented generation systems, developing applied ML models, and collaborating with SaaS partners and Microsoft AI services to deliver production-grade AI solutions.

Requirements

• Minimum 5+ years of experience in data science, machine learning engineering, or applied AI
• Experience building and deploying LLM-powered applications in production environments
• Expert-level proficiency in Python and SQL
• Experience with cloud ML platforms (Azure ML, AWS SageMaker, or GCP Vertex AI)
• Foundation in classical ML (regression, classification, clustering, time series forecasting) and statistical methods
• Experience with at least one agentic AI or LLM orchestration framework
• Four-year degree in Data Science, Computer Science, Statistics, Mathematics, or related field

Nice To Haves

• Experience with the Microsoft AI ecosystem: Azure OpenAI, Azure AI Search, Azure ML, Microsoft Fabric, Copilot Studio, Semantic Kernel
• Master’s or PhD in a quantitative field
• Experience building AI solutions for sales, customer service, supply chain, or operations use cases
• MLOps experience: CI/CD pipelines for model deployment, experiment tracking (MLflow), model monitoring and retraining
• Experience with deep learning frameworks (PyTorch, TensorFlow) for NLP or document intelligence tasks
• Experience in electrical distribution, wholesale distribution, manufacturing, or B2B operations
• Familiarity with SAP S/4 HANA data structures or ERP data integration
• Experience collaborating with AI SaaS vendors while building proprietary capabilities

Responsibilities

• Design, build, and deploy agentic AI solutions for sales, customer service, procurement, and operations using Azure OpenAI, Copilot Studio, and Semantic Kernel.
• Develop, validate, and deploy ML models for business use cases including demand forecasting, classification, anomaly detection, and optimization.
• Implement retrieval-augmented generation architectures on Microsoft tooling, including chunking strategies, embedding models, vector search, and hybrid retrieval.
• Own the ML lifecycle end-to-end: experiment tracking, model registration, deployment, monitoring, and retraining using Azure ML with CI/CD in Azure DevOps.
• Develop prompt engineering strategies, evaluate LLM outputs, and implement guardrails to minimize hallucination and ensure accuracy in production.
• Partner with data engineering teams and SaaS vendors (Canals.ai, Fragment.ai) to improve data pipelines, evaluate vendor model performance, and build proprietary capabilities where warranted.
• Collaborate with AI Product Owners and the GenAI team to translate business problems into data science workstreams, provide technical guidance for Copilot Studio makers, define success metrics, and validate business value.
• Present model results, AI capabilities, and recommendations in terms that non-technical business leaders understand and can act on.
• Effectively collaborate and communicate with all team SMEs.

Benefits

• Multiple plan options for Medical, Dental, Vision, and Prescription Drug benefits.
• Life Insurance coverage for you and options for your family.
• Flexible Spending Accounts
• Disability Benefits
• Profit Sharing Plans
• 401(k) Savings Plan with company match
• Paid Vacation & Sick Days
• Paid Holidays
• Paid Wellness Day
• Community Time Off
• Educational Reimbursement
• Career Development Programs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior