- Developing ML/AI/GenAI models and solutions.
- Performing data gathering, mining, and processing on large volumes of data; creating appropriate data models.
- Demonstrating breadth of knowledge in the application of ML/AI/GenAI and statistical methods to solve business problems.
- Conducting research on data model optimization and algorithms to improve effectiveness and accuracy of data analyses.
- Interacting and collaborating with team members and colleagues outside the organization.
- Participating in 1-2 projects concurrently.
- Holding a strong focus on continual learning in the Analytics field.
- Analytical Thinking: Extensive knowledge of techniques and tools for effective analysis; ability to determine root cause of problems and create alternative solutions.
- GenAI / AI / Machine Learning: Working experience and knowledge of principles, technologies, and algorithms of GenAI, AI, and machine learning; ability to develop, implement, and deliver related systems, products, and services.
- Statistics: Extensive knowledge of statistical tools, processes, and practices to describe results on measurable scales; ability to use statistical tools and processes to assist in making business decisions.
- Programming Languages: Working experience in applying Python (NumPy, SciPy, Pandas, etc.) to solve business challenges; ability to use tools, techniques, and platforms to write and modify programming languages.
- Information Processing: Experience in processing large quantities of detailed information with high levels of accuracy.
- Presentation Skills: Ability to summarize and present results effectively.
- A Bachelor's, Master's, or Ph.D. degree, preferably in statistics, economics, mathematics, or a similar field with quantitative coursework.
- 3-4+ years of professional experience utilizing quantitative analysis, or a Master's degree with 2+ years of experience.
- Experience with data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc.
- Practical applications of machine learning techniques such as clustering, logistic regression, CART, random forests, SVM, or neural networks.
- Technical and problem-solving skills with evidence of continuous learning in the analytics field.
- Breadth and depth of knowledge in the application of statistical and/or digital methods to solve business problems.
- Experience with projects connecting data from various business domains and providing forecasts and insights to run the business profitably.
- Working knowledge of cloud technologies (AWS, Azure, Google Cloud, etc.).
- Working knowledge of version control/repositories such as GitHub.
- Experience operating in an Agile environment.
- Initiative to research and apply new methods and digital technologies to exceed customer expectations.
- Good communication, interpersonal, and collaboration skills.
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Data Scientist - Irving - Caterpillar

Description
Job Summary:
Your work shapes the world at Caterpillar Inc.
You will join a global team that cares not just about the work we do, but also about each other. We are makers, problem solvers, and future world builders creating stronger, more sustainable communities. We make progress and innovation happen with our customers, where we work and live.
Role Definition
You will be a technical expert working in a team environment to support the development, integration, and enhancement of Caterpillar's analytics, AI, and Generative AI projects and products.
Responsibilities:
Skills Descriptor:
Top Candidates Will Also Have:
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