Data Scientist - Autonomy & Automation @ Caterpillar Inc.
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Job Details
Overview
Join Caterpillar Inc. as a Data Scientist - Autonomy & Automation. You will contribute to building a better world through data mining, enhanced data collection, statistical analysis, and machine learning. Work with state-of-the-art methods to drive business insights and innovation in a dynamic engineering environment.
Key Responsibilities
- Perform data mining and processing to create analytical systems.
- Enhance data collection and ensure data integrity for analysis.
- Develop ad-hoc analysis and present clear results.
- Build, optimize, and document machine learning models.
- Create automated anomaly detection systems with performance tracking.
- Design REST APIs and manage machine learning pipelines.
- Provide technical leadership and project guidance.
- Consult with customers to improve operational processes.
Qualifications
Basic Qualifications: Bachelor’s degree or equivalent experience; 5+ years of relevant experience; strong analytical, math, and problem-solving skills; expertise in Python and familiarity with git; experience in building REST APIs and working in development teams; and proficiency in SQL and applied statistics.
Desired Qualifications: Master’s Degree, extensive data mining experience, advanced pattern recognition, predictive modeling skills, and familiarity with data science toolkits and frameworks such as Jupyter Notebook, AWS Sagemaker, and data visualization tools.
Key skills/competency
- Data Mining
- Machine Learning
- Python
- SQL
- Statistical Analysis
- Data Visualization
- REST API
- Technical Leadership
- Feature Engineering
- Predictive Modeling
How to Get Hired at Caterpillar Inc.
🎯 Tips for Getting Hired
- Customize your resume: Tailor it to data science and machine learning skills.
- Showcase project leadership: Highlight technical leadership experiences.
- Prepare for technical interviews: Emphasize Python and algorithms expertise.
- Research Caterpillar Inc.: Understand company culture and digital strategy.