Data Scientist Ii

Do you want to help solve the world's most pressing challenges? Feeding the world's growing population and slowing climate change are two of the world's greatest challenges. AGCO is a part of the solution Join us to make your contribution.

The Data Scientist role is responsible for the development and execution of data science and analytics use cases at AGCO. The Data Scientist executes the research, modeling design, implementation, and supports the deployment of full-stack scalable AI solutions to critical business opportunities. The Data Scientist will develop and implement machine learning algorithms and statistical models to solve business problems, and perform exploratory data analysis to identify trends, patterns, and anomalies. Collaboration is key, and the data scientist will work closely with cross-functional teams to understand business requirements and translate them into data-driven solutions. The ability to communicate findings and insights through data visualizations and presentations will be essential in driving informed decision-making across the organization. Additionally, the data scientist role will stay up to date with the latest advancements in data science, machine learning, and artificial intelligence, ensuring that our methodologies and tools remain cutting-edge. These contributions will be vital in maintaining the integrity of our data throughout its lifecycle and in fostering a culture of continuous learning and innovation within the team.

**Your Impact**
- Insight Identification: Collaborate with the AI Delivery Owner and key business stakeholders to identify and prioritize actionable and impactful insights across various core business areas, driving informed decision-making.
- Methodology Selection: Determine the most appropriate AI/ML techniques for addressing different classes of business problems and assess the feasibility of analytics use cases through proof-of-concept (POC) studies.
- Opportunity Translation: Translate business opportunities, needs, or hypotheses from partners into actionable tasks, effectively converting business requirements into mathematical and computational steps to deliver insights.
- Solution Development: Develop analytics solutions that align with business goals, ensuring statistical integrity and implementing accuracy tracking and lifecycle management techniques.
- Deployment Collaboration: Work closely with cloud and data engineers to deploy and integrate analytics-based solutions using scalable, high-performance, and cost-efficient machine learning pipelines.
- Actionable Insights: Map analytical insights into actionable recommendations, clearly communicating the implications of results. Leverage business knowledge and storytelling to enhance adoption among end users.
- Change Advocacy: Act as a change agent by engaging with business stakeholders and the data science community to educate, raise awareness, and build support for world-class data and analytics practices.
- Continuous Learning: Stay current with leading data science and analytic practices, trends, design methodologies, and development cycles.
- Leadership: Provide leadership and direction to the junior data scientists, by fostering a collaborative environment and ensuring the continuous growth of their skills and capabilities

**Your Experience and Qualifications**
- 7+ years of experience in a related field with hands-on experience in the development of analytical models and machine learning techniques.
- Proven track record (3+years) of implementing and leading complex data science and analytics projects to completion/production.
- Technical proficiency in languages such as Python, R, etc. Familiarity with big data tools such as Hive, Spark, Hadoop etc.
- Deep understanding of machine learning algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience in data mining and predictive modeling inclusive of linear and non-linear regression, logistic regression, and time series analysis models.
- Experience working with deep learning algorithms and large datasets as well as experience working with unstructured data and experience cleaning and manipulating data.
- Strong data visualization and communication skills including written, verbal and presentation skills.
- Knowledge and expertise working with relational databases and large datasets, along with the data governance and quality management processes need to improve quality of the analysis.
- Understanding of current state and future trends in data analytics, data science and enabling technologies
- Able to creatively approach problems and work through ambiguity to guide business partners through the art of the possible to tangible business value with analytics. Thrives in innovating around new white spaces.
- Strong academic qualifications, including advanced understanding/coursework in Mathematics, Statistics, Data Science, Technology, Engineering, Economics, or related field.

**Your Benefits**
- GLOBAL DI