Staff Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Scientist based in the United States. As a Staff Data Scientist, you will provide technical leadership in evaluating the performance and impact of advanced technologies, including precision agriculture, automation, autonomous systems, and digital products. You will lead a team of data scientists while remaining hands-on in developing machine learning models, analytical solutions, and data pipelines. Working with large-scale operational and environmental datasets, you will transform complex information into actionable insights and measurable business outcomes. You will take initiatives from early-stage exploration to production-ready solutions, establishing rigorous evaluation methods and performance benchmarks. Collaborating with product, engineering, and business leaders, you will influence technology strategies and investment decisions. This remote opportunity offers the chance to shape innovation in an environment focused on solving large-scale challenges through data, AI, and advanced engineering. 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 s