Staff Data Scientist

Accountabilities: As a Staff Data Scientist, you will lead technical initiatives, oversee performance evaluation strategies, and help translate complex data into meaningful improvements across technology products. Your main responsibilities will include: Lead a sub-team of data scientists within the Technology Intelligence Proving Ground, establishing priorities, allocating responsibilities, and providing day-to-day technical guidance. Define the technical strategy for evaluating the performance of machines, precision technologies, automation and autonomous capabilities, and digital products. Design and conduct structured technology evaluations and benchmarks using repeatable methodologies, clear success criteria, and measurable outcomes. Drive projects from initial concepts to tangible business results by framing problems, exploring data, developing prototypes, and delivering scalable solutions. Independently develop machine learning models, analytical solutions, and data pipelines to assess real-world technology performance. Leverage PAAW datasets to engineer features that capture machine, operational, and environmental context and connect these factors to technology usage. Conduct exploratory data analysis (EDA) to understand unfamiliar datasets, identify data quality issues, and uncover valuable patterns and opportunities. Maintain comprehensive documentation of technology evaluations, performance results, and supporting evidence. Collaborate with product, engineering, and business stakeholders to align evaluation initiatives with strategic priorities and inform technology investments. Present findings and actionable recommendations to product and engineering teams, providing the evidence needed to drive improvements. Maintain a transparent work backlog, actively contribute to Agile processes, and communicate progress, risks, and priorities. Mentor data scientists and engineers through technical coaching, design reviews, code reviews, and knowledge-sharing initiatives. Communicate technical findings and strategic recommendations effectively to senior leadership and cross-functional teams. Requirements : The ideal candidate combines advanced data science expertise, strong software engineering capabilities, and proven technical leadership. You should be comfortable navigating ambiguity, working independently, and translating complex analytical challenges into measurable business outcomes. The key qualifications include: At least 2 years of relevant experience with a PhD, 3 years with a Master's degree, or 5 years with a Bachelor's degree. Significant experience developing and delivering production-grade machine learning, deep learning, AI, advanced analytics, or data-intensive software solutions. Demonstrated success taking ambiguous ideas from initial exploration to implementation and measurable business impact. Strong ability to navigate incomplete requirements, evolving priorities, and unfamiliar problem spaces while maintaining progress. Existing knowledge of the organization's technologies, products, data platforms, and PAAW datasets. Practical experience using PAAW data to develop features that capture machine, operational, and environmental context. Expertise in connecting technology usage data with relevant conditions, including machine configuration, operating practices, field conditions, weather, and terrain. Strong exploratory data analysis skills and the ability to work efficiently with large, complex, or unstructured datasets. Experience designing and executing product or technology performance evaluations, benchmarks, and evidence-based assessments. Advanced programming skills and solid knowledge of machine learning, statistics, experimentation, model validation, and performance measurement. Strong software engineering fundamentals, including version control, automated testing, CI/CD, reproducibility, and maintainable code. Previous experience leading teams or technical workstreams, setting priorities, delegating responsibilities, and developing team members. Experience working in Agile environments using tools such as Azure DevOps, Jira, or equivalent platforms. Proficiency with AI-assisted development tools, including GitHub Copilot, coding agents, and LLM-based assistants, with the ability to validate AI-generated outputs for accuracy and quality. Excellent written and verbal communication skills, particularly when presenting technical assessments and recommendations to senior stakeholders. Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Operations Research, or a related technical discipline, or equivalent professional experience. An advanced degree in statistics, mathematics, engineering, computer science, a quantitative discipline, or applied AI/ML is highly preferred. Additional experience that would be considered an advantage: Professional experience in agriculture, construction, forestry, or other heavy equipment industries. Familiarity with digital products and technologies such as machine telemetry, precision agriculture, Operations Center, JDLink, autonomy, and perception systems. Experience working within established architecture, security review, and data governance frameworks. Experience handling large-scale datasets, including geospatial information, imagery, time-series data, machine telemetry, operational data, or agronomic datasets. Background in product performance analytics, field testing, validation and verification, or proving ground operations. Specialized 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. Knowledge of responsible AI, privacy, cybersecurity, data governance, and model governance practices. Benefits : Competitive annual base salary ranging from $123,804 to $185,700, depending on qualifications and experience. Flexible work arrangements and remote working opportunities. Comprehensive healthcare benefits, including generous employer contributions to Health Savings Accounts. 401(k) savings and retirement benefits, including a Defined Contribution plan. Vacation and paid holiday leave. Adoption assistance programs. Employee Assistance Programs. Tuition assistance and professional development support. Fitness subsidies and access to on-site gyms at selected locations. Charitable contribution matching. Employee Purchase Plan and various personal discount programs. Inclusive working environment with opportunities to explore new projects, develop professionally, and work with advanced technologies.