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.

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
Preferred 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

Multiple plan options for Medical, Dental, Vision, and Prescription Drug benefits.
Life Insurance coverage for you and options for your family.
Save on expenses with Flexible Spending Accounts.
Enjoy our Disability Benefits at no cost to you.
Share in our success with Profit Sharing Plans.
401(k) Savings Plan with company match to help secure your future.
Paid Vacation & Sick Days to spend time away from work or in case of an illness.
Rest and recharge during our Paid Holidays throughout the year.
Take advantage of our Paid Wellness Day to focus on preventive care and prioritize your health.
Volunteer with Community Time Off to give back to the community.
Predictable Work Schedules to plan your life: no weekends or nights for most roles.
Celebrate your and others' achievements with our Employee Recognition Program.
Reach your career goals with our Educational Reimbursement and Career Development Programs.
And More Perks that support your well-being and career growth.

Senior Data Scientist

Key skills