Staff Data Scientist

 
As a Staff Data Scientist for John Deere Inteligence Solutions Group located in Urbandale, IA, you will:
 

• Lead a sub-team of data scientists within the Technology Intelligence Proving Ground, setting priorities, assigning work, and providing day-to-day technical leadership.
• Define the technical strategy for how the proving ground evaluates and measures the performance of the John Deere technology suite, including its machines, precision technologies, automation and autonomy features, and digital products.
• Design and run structured performance evaluations and benchmarks of John Deere technologies, with repeatable methods, clear success criteria, and measurable outcomes.
• Take vague ideas from 0 to 1: frame the problem, explore the data, build a working prototype, and carry it through to measurable business impact.
• Operate independently and self-directed. Set your own priorities within the proving ground's goals, and judge how often and when to check in with leadership and stakeholders.
• Personally build models, analyses, and data pipelines that measure how John Deere technologies perform in real-world use, using John Deere data including PAAW datasets.
• Use PAAW datasets to engineer features that capture machine, operational, and environmental context, and associate that context with technology usage to explain how and where each technology performs.
• Lead exploratory data analysis (EDA) to quickly understand new and unfamiliar datasets, surface data quality issues, and identify promising signals.
• Maintain a record of what has been evaluated, the performance results, and the evidence behind each finding across the John Deere technology suite.
• Partner with product, engineering, and business leaders to align evaluations with business priorities and inform product and technology investment decisions.
• Deliver performance findings and improvement recommendations to the product and engineering teams that own each technology, with the documentation and evidence they need to act.
• Maintain an accurate and transparent backlog of your work, and commit to working in an Agile environment as a champion of the process.
• Mentor data scientists and engineers through design reviews, code reviews, technical coaching, and knowledge sharing.
• Communicate findings, risks, and recommendations clearly to technical teams and senior leaders.

VISA Sponsorship is NOT available for this position

• Minimum of 2 years of experience with PhD, 3 years with Master of Science degree, or 5 years with Bachelor's degree.
• Significant experience creating and delivering production-grade machine learning, deep learning, AI, advanced analytics, or data-intensive software solutions.
• Proven track record of taking a vague idea from 0 to 1 and turning it into measurable business impact.
• Demonstrated ability to navigate ambiguity: making progress with incomplete requirements, shifting priorities, and unfamiliar problem spaces.
• Existing knowledge of John Deere technologies, products, and data platforms.
• Existing working knowledge of PAAW datasets, including experience using them to build features that capture machine, operational, and environmental context.
• Experience with feature engineering that links usage data to the conditions it occurred in, such as machine configuration and state, operating practices, and field, weather, or terrain conditions.
• Strong exploratory data analysis (EDA) skills, with the ability to navigate large, unfamiliar, or messy datasets effectively and quickly.
• Experience designing and running technology or product performance evaluations and benchmarks, and drawing sound, evidence-based conclusions from the results.
• Advanced programming proficiency and strong knowledge of machine learning, statistics, experimentation, model validation, and performance evaluation.
• Strong software engineering foundation, including version control, automated testing, CI/CD, reproducibility, and maintainable code.
• Experience leading a team or workstream, including setting priorities, delegating work, and developing team members.
• Experience operating on an agile team using work management software such as Azure DevOps (ADO), Jira, or similar tools.
• Proficiency using AI tools, such as GitHub Copilot, coding agents, and LLM-based assistants, to enhance productivity and accelerate delivery, while reviewing AI-generated work for accuracy and quality.
• Strong written communication, including technical assessments and recommendations written for senior leaders.

• Experience at John Deere, or in agriculture, construction, forestry, or other heavy equipment industries.
• Experience with John Deere data and digital products, such as John Deere Operations Center, JDLink machine telemetry, precision agriculture, or autonomy and perception systems.
• Experience working within John Deere's architecture and security review processes and data governance practices.
• Experience working with large, complex datasets such as machine telemetry, geospatial data, imagery, time-series, operational, or agronomic data.
• Experience with product performance analytics, field testing, validation and verification, or running a proving ground.
• Expertise in computer vision, geospatial analytics, remote sensing, time-series modeling, optimization, robotics, autonomy, simulation, generative AI, or edge computing.
• Experience with Databricks, Spark, Kubernetes, distributed computing, model registries, or production model monitoring.
• Familiarity with responsible AI, privacy, data governance, cybersecurity, and model governance.

Ideally, you will have a degree or equivalent related work experience in the following:

• Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Operations Research, or a related technical discipline, or equivalent related work experience.
• Advanced degree in statistics, mathematics, a quantitative field, engineering, computer science, or an applied AI/ML discipline highly preferred.