Sr Data Scientist

What you'll work on

• Develop, implement, and deploy state-of-the-art ML/AI models and imaging technologies in digital pipelines for key vegetable projects with scientists and engineers across Crop Science research and development (R&D);
• Use advanced imaging-based analytical models, machine learning and AI algorithms, operations research techniques, and strong business acumen to deliver insight, recommendations, and solutions;
• Lead imaging-based project by designing and conducting the experiments, and effectively communicate the project milestones, insights and timelines with other teams and update the key stakeholders in a timely manner;
• Develop DL/AI models to simulate crop performance simulations using genetic, environmental and digital phenotyping datasets
• Develop sustainable, accurate, and impactful reporting on imaging model inputs/outputs, business impact, and key performance indicators;
• Deploy containerized ML/AI models for inference workflows
• Demonstrate full autonomy in developing relationships for effective cross-functional collaboration throughout multiple organizations and partner on work stream initiatives for Data Science Community;
• Assess needs and recommend experiments and projects, suggests new algorithmic development, drive tactical decisions about approaches and needed data;
• Present compelling, validated stories to all levels of organization, including peers, senior management, and internal customers to drive both strategic and operational changes in business;
• Develop Code: (20-25%), Stats/Modeling Research: (30-35%), Domain Knowledge and Consulting Industry Experts: (30-35%), Provide Technical Guidance to Associate DS and DS, mentors, develops and delivers presentations and strategies: (10-15%).

What we're looking for

Education/Experience

• Bachelors degree with 8 years of experience or Masters degree with 6+ years experience or PhD with 3 years of experience.

Skills (Technical & Soft)

• Educational preparation or applied experience in at least one of the following areas: Machine Learning/Deep Learning, Artificial Intelligence, Imaging Science, Computer Vision, Photogrammetry and Crop Simulation.
• Advanced competencies in image processing, computer vision, color spaces, and photogrammetric modeling.
• Solid understanding of machine learning and deep neural network algorithms and advanced statistics including regression, time-series forecasting, clustering, decision tress, exploratory data analysis methods, simulation, optimization.
• Advanced experience in ML/DL modeling and conduct analysis of high dimensional and multi-layered geospatial data layers from cutting edge imaging modalities including: multispectral, hyperspectral, LIDAR, thermal sensors.
• Demonstrate knowledge on digital twin simulation concepts and how DL/AI and physical system models can be used for crop simulations.
• Developing and improving models for computer vision projects from video, still images ortho-mosaics either post-harvest or on-plant for plant related phenotyping.
• Strong background on ML and deep learning frameworks (i.e.,XGBoost, PyTorch or TensorFlow) specifically in applying them to time-series or spatial data.
• Developing automated processing workflow or pipeline to correct for the presence of image distorting artifacts, occlusion with suitable QA/QC and analytics to deliver business outcomes.
• Strong proficiency in computational skills to build models using Python or other statistical and/or mathematical programming packages.
• Strong proficiency in model deployment using Docker and familiarity with model orchestration
• Advanced experience in a cloud computing environment (AWS, GCP) and handling large datasets.
• Extensive experience in successful delivery of valuable analysis through application of domain knowledge; evidence of strong business acumen.
• Experience working within Agile Scrum framework
• Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise and actionable manner to broad audiences and key stakeholders across multiple functions.
• Strong interpersonal skills to work with and support global colleagues asynchronously