Senior Data Scientist
Milwaukee, Wisconsin, United States
- Pay
- Pay not listedSimilar roles state $118K–$193K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingBuild labeled datasets from operational data such as logs, sensors, and documents
Build, validate, and maintain predictive models used as agent tools
Own the data pipeline for retrieval-augmented generation knowledge bases
Build evaluation frameworks for retrieval quality and factual accuracy
Apply causal inference methods to isolate effects in operational environments
From the employer’s posting
Build high-quality labeled datasets from operational data sources including structured databases, event logs, sensor streams, and document repositories
Build, validate, and maintain predictive models (e.g. anomaly detection, classification, forecasting) that serve as callable tools within agentic AI systems
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
Apply relevant causal inference techniques (e.g. synthetic controls, difference-in-difference) to isolate causal effects in operational environments
Education & alternatives
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.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- GCP
- pandas
- PyTorch
- scikit-learn
Source — Tool mentions in context
• 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
Benefits in the posting
Full benefits wording- Health Insurance including Medical, Dental and Vision
- 401k
- Paid Time off
- Parental and Caregiver Leave
- 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.
From the employer’s posting.
Posting record
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- Live
- First seen by us
- Aug 11, 2026 · 79 days ago
- Recorded sightings
- 224
- Last seen by us
- Oct 30, 2026
- Employer says posted
- Jul 28, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better.
We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us!
Job Description
Job Description
The Data Science & Innovation Organization is building the analytical engine that powers our AI product portfolio. As Senior Data Scientist, Agentic AI Products, you will own the data and modeling layer that our agentic systems depend on. This role sits directly alongside the Senior Agentic AI Engineer, who designs and deploys the reasoning, orchestration, and tool-use layers of our AI agents. Where that role builds the agent architecture, you build the empirical foundation. The empirical foundation consists of curated datasets, predictive models embedded as agent tools, statistical rigor for evaluation, and the feedback infrastructure that makes agents measurably better over time. Together, these two roles form the core of our applied AI capability.
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.
#LI-Hybrid
#LI-LifeAtRok
#LI-SB1
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Milwaukee, Wisconsin, United States
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. #LI-Hybrid #LI-LifeAtRok
More source context
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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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