Bobcat Company is a manufacturer of farm and construction equipment and a sub-organization of Ingersoll Rand. As a Data Scientist, you will apply advanced statistical and computational methods to solve real-world business problems, enabling data-driven decision-making across the organization.
Develop machine learning and artificial intelligence applications, with an emphasis on the production of intuitive user experiences characterized by clean design and ease of use.
Implement best practices of MLOps to ensure the reliability, scalability, and performance of machine learning models in production environments.
Collaborate with external partners to accelerate development and deployment of data science solutions, leveraging complementary capabilities and resources.
Incorporate the latest advanced analytics processes learned from external partners into our internal workflows and methodologies, ensuring that our data science practices remain at the forefront of industry innovation.
Research, develop, and deploy advanced machine learning algorithms and predictive models to solve complex business problems.
Explore novel techniques and methodologies to enhance the performance, scalability, and robustness of our data science solutions.
Identify relevant data sources and variables for analysis, leveraging both structured and unstructured data, to generate key insights for business improvement.
Qualification
Required
Bachelor’s Degree in a quantitative discipline, such as Data Science, Mathematics, Computer Science, Engineering, or a related field with applicable skills.
2+ years of related work experience
Strong problem-solving abilities.
Curiosity with the ability to learn and apply new technologies.
Demonstrated proficiency in programming language(s), preferably Python.
Excellent teamwork/collaborative aptitude, with the ability work independently.
Preferred
Experienced use of AWS
Experienced use of Azure
Benefit
Bobcat Company is a manufacturer of farm and construction equipment. It is a sub-organization of Ingersoll Rand.
