Sr Data Scientist

Join to apply for the Sr Data Scientist role at Bayer . Pourpose Bayer is looking for a Senior Data Scientist to join the Data Science and Engineering Capability Center in Bayer Euroservices within the Crop Science hub. This role will develop state-of-the-art ML/AI models in support of advancing new products through the R&D pipeline and generating new insights for R&D stakeholders. Key Tasks & Responsibilities 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%). Key Working Relations Building relationships and networks within current function and cross‑functionally, interacts most often with Data Scientists across multiple organizations and key stakeholders within the business including senior level management. Active member in the Data Science community to build personal acumen & ability, while also sharing new industry best practices in data science methodologies. Provides support for their team without management presence and is expected to provide technical leadership to all levels of the organization. Qualifications & Competencies Education and 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. Application Period 23/12/2025‑09/01/2026 Reference Code Division Crop Science Location Spain: Cataluña: Barcelona Functional Area Engineering & Technology Position Grade VS 1.2 Employment Type Regular Work Time Full time Seniority level Mid‑Senior level Job function Engineering and Information Technology Industries Chemical Manufacturing, Pharmaceutical Manufacturing, and Biotechnology Research #J-18808-Ljbffr