Senior Data Scientist

Primary Responsibilities:

Dataset creation & curation

• Build high-quality labeled datasets from operational data sources including structured databases, event logs, sensor streams, and document repositories
• Define feature engineering strategies for time-series, event-based, and unstructured data

Predictive model development

• Build, validate, and maintain predictive models (e.g. anomaly detection, classification, forecasting) that serve as callable tools within agentic AI systems
• Apply rigorous statistical methods: hypothesis testing, cross-validation, and confidence interval estimation to ensure model outputs are trustworthy when surfaced by an agent

Agent data interfaces & RAG grounding

• Own the data pipeline that populates structured knowledge bases used for retrieval-augmented generation in agentic products
• Build evaluation frameworks to measure retrieval quality and factual accuracy against domain specific ground-truth datasets

Experimentation & statistical rigor

• Apply relevant causal inference techniques (e.g. synthetic controls, difference-in-difference) to isolate causal effects in operational environments
• Serve as the statistical conscience of the AI team: design measurement frameworks before shipping, and build internal culture around responsible AI performance claims

Cross-functional enablement

• Collaborate with product managers to translate domain use cases into well-formed ML problem statements
• Work with AI engineers and data platform teams to align on feature store standards and machine learning best practices that support reliable agent tool integration

The Essentials - You Will Have:

• Bachelor's Degree in relevant field.
• Legal authorization to work in the US is required. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

The Preferred - You Might Also Have:

Core data science foundations

• 5+ years building end-to-end predictive models in production: from raw data through feature engineering, model training, evaluation, and deployment

• Applied statistics: hypothesis testing, Bayesian methods, time-series modeling, uncertainty quantification, and understanding of common ML evaluation failure modes

• Proficiency in Python (pandas, scikit-learn, PyTorch or equivalent); advanced SQL; familiarity with cloud data platforms (AWS, GCP, or Azure)

AI agent and RAG data experience

• Direct experience building datasets and evaluation pipelines for conversational AI, chatbot, or agent systems

• Understanding of how predictive model outputs (scores, probabilitie

What We Offer:

• Health Insurance including Medical, Dental and Vision
• 401k
• Paid Time off
• Parental and Caregiver Leave
• Flexible Work Schedule where you will work with your manager to enjoy a work schedule that can be flexible with your personal life.
• To learn more about our benefits package, please visit at www.raquickfind.com.

This position is part of a job family. Experience will be the determining factor for position level and compensation.

At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles.

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We are an Equal Opportunity Employer including disability and veterans.

If you are an individual with a disability and you need assistance or a reasonable accommodation during the application process, please contact our services team at +1 (844) 404-7247.

Rockwell Automation’s hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.