Data Scientist

JOB DUTIES:

1. Typical problems include enhancing customer satisfaction by delivering key insights on customer experience, identifying sales, rental, and service opportunities for Caterpillar dealers, determining the principal drivers to maximize marketing return on investment; recommending optimum investment in each marketing channel.
2. The principal responsibility of the Data Scientist is to be an independent contributor to multi-person analytic teams. This position has a depth of knowledge in quantitative analytic methods, data management, and or associated digital technologies suitable to handle all but the most complex issues. Data Scientist is expected to be familiar with the company’s processes, products, and organization, as well as its customers, competitors, and stakeholders. Work is typically directed by a direct supervisor, project or team lead through a review of results. Decisions on routine, medium risk issues that may affect the project team, suppliers or internal customers may be made by this position. Challenges include meeting expectations in delivering results, learning to refine solutions to better fit complex situations, making timely decisions, and communicating effectively with all project stakeholders. The Data Scientist also mentors and develops the capabilities and organizational knowledge of junior data scientists and associates.
3. The Data Scientist demonstrates thorough knowledge of statistical approaches, data management techniques, and/or related digital technologies, and the ability to handle complex issues. The incumbent demonstrates very good communication and presentation skills, being able to explain conclusions to customers who have limited knowledge and experience with quantitative analytical methods. As an individual contributor on teams, they should also exhibit strong initiative and teamwork skills, and a comprehensive knowledge of Caterpillar Inc., its products and services; its internal systems, processes, and procedures; and the external environment in which it competes.
4. Background/Experience:
5. Bachelor’s degree, preferably in AI, Data Science, Computer Science, Statistics or a similar field with quantitative coursework, and 4-5 years of marketing analytics experience utilizing quantitative analysis, a Master’s degree and 2-4 years of experience, or a PhD in one of the associated fields.
6. Strong understanding of machine learning algorithms, data structures, and statistical methods.
7. Experience with deep learning techniques and neural networks
8. Ability to work with large datasets in cloud environment and perform data preprocessing and feature engineering.
9. Proficiency in Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
10. Experience in designing, developing, deploying Machine Learning models using AWS Sage Maker.