Data Scientist

Data Scientist Job Type: W2, 3-month Contract Job Location: Onsite in Urbandale, IA Position Overview As a Data Scientist within the client’s Intelligent Services Group (ISG), you will work with petabyte-scale datasets to build advanced analytics and machine learning models that enable intelligent, automated equipment and better decision-making for farmers. You’ll collaborate with product managers and data engineers to deliver full-stack data science solutions that make a real-world impact. Key Responsibilities • Communicate findings and methodologies effectively to stakeholders across disciplines. • Work with high-resolution machine and agronomic data to develop and test predictive models. • Deliver production-ready machine learning solutions that generate insights from precision agriculture data. • Define and analyze Key Performance Indicators (KPIs) that reflect successful customer outcomes. • Collaborate with Data Engineering teams to ensure efficient data storage and analytics support. Required Skills • Proficiency in developing production-ready models using object-oriented programming (e.g., Python). • Experience with data-access technologies such as SQL, Spark, Databricks. • Familiarity with visualization tools like Tableau, Kepler.gl. • Knowledge of data modeling techniques including normalization, data quality assessment, and performance management. • Experience building machine learning models (e.g., regression, supervised/unsupervised learning, probabilistic inference, NLP). • Strong communication skills for leading meetings, documenting work, and presenting concepts clearly. Preferred / Stand-Out Skills • Experience with geospatial data search and analysis, geo-indexing, vector/raster structures. • Familiarity with remote sensing, GIS tools, and satellite imagery analysis. • Background in computer vision and machine learning (CVML). • Exposure to advanced AI techniques and tools. • Portfolio of professional work (e.g., publications, patents, project samples). • Experience with distributed datasets and diverse data structures (e.g., time-series, geo-tagged, text, structured/unstructured). • Additional programming languages (e.g., Java, JavaScript, Scala). • Experience with simulations (e.g., Monte Carlo, Gibbs sampling). • Skills in model validation, bias/drift measurement. • Ability to collaborate with cross-functional teams (Product, Sales, Finance). • Ability to explain complex analytics to non-technical audiences.