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SeniorFull-timeMachine LearningData ScienceGitAIML
Salary Range
$26,520 - $35,880 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
The Data Scientist will utilize data science techniques to solve real-world problems for Crop Protection Development (CPD) R&D and related divisions. This role involves building data science solutions by collecting, analyzing, and interpreting large datasets, including images, and developing models using deep learning and machine learning algorithms.
Key Responsibilities
- βCollaborate with cross-functional teams to understand business requirements and design end-to-end solutions architecture for data science applications.
- βUtilize crop protection trial data (text, numeric, and images) to generate insights via dashboards, ML/DL/AI/LLM models that help field scientists, digital agronomists, and product development heads to take informed decisions.
- βPerform statistical analyses of product performance data for CPD and business needs.
- βWork closely with the Digital Agronomy team to automate field insights and query response for field scientists, farmers, and the commercial team.
- βStreamline data collection, analysis, and visualization, particularly when dealing with advanced digital instruments.
- βPartner with AMEA and Global Technical Excellence and Quantitative Biology team for development, testing, and implementation of new methodologies and applications in data projects.
- βUse BITS and other tools and systems to provide information to the CPD team in the form of data searches, queries, summaries, visualizations, analyses, and reports.
- βBuild deep learning/image recognition based advisory tools for farmers via the Cropwise grower App.
- βCollaborate with the data engineering team to seamlessly transition ML/AI innovations into scalable and reliable operational solutions.
- βPrepare technical reports and presentations to communicate results and insights to both technical and non-technical stakeholders.
- βContribute to the development and testing of mobile application/enhancement on the application for various platforms like Android, iOS, or Windows.
Requirements
- βStrong background in data science, machine learning, and deep learning.
- βExperience with statistical analysis and data visualization.
- βKnowledge of crop protection trial data and agricultural applications.
- βProficiency in using tools like BITS and other data science platforms.
- βAbility to collaborate with cross-functional teams and stakeholders.
- βExperience with mobile application development and enhancement.
