Senior Data Scientist

Posted 15 Days Ago
Milwaukee, WI, USA
In-Office
Senior level
Hardware • Software
The Role
Lead dataset creation, feature engineering, and predictive-model development for agentic AI products. Build RAG data pipelines and evaluation frameworks, apply rigorous statistical and causal-inference methods, and collaborate with product, engineering, and platform teams to integrate reliable model tools into agent systems.
Summary Generated by Built In

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.

Skills Required

  • Bachelor's degree in a relevant field
  • Legal authorization to work in the US (no visa sponsorship available)
  • 5+ years building end-to-end predictive models in production
  • Applied statistics knowledge (hypothesis testing, Bayesian methods, time-series, uncertainty quantification)
  • Proficiency in Python (pandas, scikit-learn, PyTorch or equivalent)
  • Advanced SQL
  • Familiarity with cloud data platforms (AWS, GCP, or Azure)
  • Experience building datasets and evaluation pipelines for conversational AI/chatbot/agent systems and RAG grounding
  • Experience applying causal inference techniques (synthetic controls, difference-in-difference)

Rockwell Automation Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Rockwell Automation and has not been reviewed or approved by Rockwell Automation.

  • Healthcare Strength Healthcare coverage is described as comprehensive, spanning medical, dental, vision, mental‑health support, disability and life insurance, and wellness resources. Multiple plan choices and supportive programs contribute to the package feeling well‑rounded.
  • Retirement Support Retirement benefits include a 401(k)/Retirement Savings Plan with employer matching that is positioned as a meaningful part of total compensation. These offerings reinforce longer‑term financial security as a core strength.
  • Parental & Family Support Paid parental leave was expanded and a paid caregiver leave was added, indicating clear support for family needs. These policies are complemented by flexibility signals and dedicated paid volunteer time.

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The Company
HQ: Milwaukee, WI
22,000 Employees
Year Founded: 1903

What We Do

At Rockwell Automation, we connect the imaginations of people with the potential of technology to expand what is humanly possible, making the world more intelligent, more connected and more productive.

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