Senior Data Scientist, AI Research & Development

Qualifications

• Extensive knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions
• Accuracy and Attention to Detail:
• Extensive understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision
• Working knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems
• Extensive knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services
• Programming
• Working knowledge of basic concepts and capabilities applying Python (Num Py, Sci Py, Pandas, etc) programming; ability to use tools, techniques and platforms in order to write and modify programming languages
• Extensive knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use
• Working knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project
• Experience handling unclear problems and crafting solutions despite constraints or lack of definition
• Typically, Bachelors, Masters, or PhD degree in Data Science, Predictive Analytics, Business Analytics, Business Intelligence & Analytics, Applied Statistics, Computer Science, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), Information Systems Management, Mathematics, or equivalent technical degree
• Typically, 8+ years of professional experience utilizing quantitative analysis, or a Master's degree and 6+ years of experience, or a PhD and 2+ years of experience in relevant experience
• Experience with advanced 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
• Experience in design / development of heavy equipment (ex
• automotive, aerospace, engine, transmission, construction, mining, industrial, etc)
• Strong technical and problem-solving skills and 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
• Competency in coaching and mentoring junior Data Scientists in the creation,…

Responsibilities

• Join the Artificial Intelligence Research & Development team of Cat Digital and be responsible for performing analytical tasks and initiatives on huge amounts of data to support data-driven business decision and development
• Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models
• Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques
• Defining requirements and scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies
• Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses
• Designing and developing prototypes and proof-of-concepts utilizing generative artificial intelligence (genAI) to assess solution feasibility and secure business approval

Full Description

Career Area:

Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live.

Together, we are building a better world, so we can all enjoy living in it.

Cat® Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital and analytics solutions for our customers and dealers. We've created an inclusive environment for you to explore your passions, make an impact and do the work that really matters. With over 1.5M connected assets worldwide, our business and in the industries, we serve, data is generated continuously by Cat® equipment using the latest technology, advanced analytics, telematics and AI capabilities to help our customers build a better world.

Job Summary:

Join the Artificial Intelligence Research & Development team of Cat Digital and be responsible for performing analytical tasks and initiatives on huge amounts of data to support data-driven business decision and development.

What You Will Do:

Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models.

Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques.

Defining requirements and scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies.

Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses.

Designing and developing prototypes and proof-of-concepts utilizing generative artificial intelligence (genAI) to assess solution feasibility and secure business approval.

What

You Will Have:

Business Statistics:

Extensive knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.

Accuracy and Attention to Detail:

Extensive understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.

Analytical Thinking:

Working knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.

Machine Learning:

Extensive knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.

Programming

Languages:

Working knowledge of basic concepts and capabilities applying Python (Num Py, Sci Py, Pandas, etc) programming; ability to use tools, techniques and platforms in order to write and modify programming languages.

Query and Database Access Tools:

Extensive knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.

Requirements Analysis:

Working knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.

Comfort with Ambiguity:

Experience handling unclear problems and crafting solutions despite constraints or lack of definition.

Considerations for Top Candidates:

Typically, Bachelors, Masters, or PhD degree in Data Science, Predictive Analytics, Business Analytics, Business Intelligence & Analytics, Applied Statistics, Computer Science, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), Information Systems Management, Mathematics, or equivalent technical degree.

Typically, 8+ years of professional experience utilizing quantitative analysis, or a Master's degree and 6+ years of experience, or a PhD and 2+ years of experience in relevant experience.

Experience with advanced 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. Experience in design / development of heavy equipment (ex. automotive, aerospace, engine, transmission, construction, mining, industrial, etc)

Strong technical and problem-solving skills and 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

Competency in coaching and mentoring junior Data Scientists in the creation,…