Data Scientist

Purpose

• Be integral part of the P&S Data Science team that applies technical expertise in data management, data science, machine learning, artificial intelligence, and automation to design, build, deploy, and maintain solutions across multiple countries.
• Work with project teams and SMEs to understand business requirements and develop appropriate data and AI/ML solutions.
• Contribute solutions with explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques to existing and new projects.
• Work independently to build applications for data collection and processing, exploration and visualization, analysis, regression, classification, and generation as required by the project and business teams.

Accountabilities

• Develop and implement complex statistical models, machine learning algorithms, and data mining techniques to extract insights from large datasets.
• Lead data science projects from conception to completion, defining scope, methodology, and deliverables.
• Collaborate with business leaders to translate data insights into actionable strategies and recommendations.
• Guide and mentor junior data scientists, fostering their professional development and technical skills.
• Contribute to the design and improvement of data architecture, pipelines, and storage solutions.
• Stay current with the latest advancements in data science and introduce new techniques or technologies to the organization.
• Establish and maintain standards for data quality, documentation, and ethical use of data.
• Present complex findings to both technical and non-technical audiences, including executive leadership.
• Address complex business challenges using data-driven approaches and creative solutions.
• Improve the efficiency and scalability of data processing and model deployment.
• Develop deep knowledge in Syngenta s P&S operations to better contextualize data insights.
• Own the design, build, and deploy process including collaboration with users and multi-disciplinary teams to fulfil the user, business and technical requirements.