Data Scientist I

Caterpillar

Chicago (IL)

On-site

USD 89,000 - 145,000

Full time

3 days ago

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Benefits offered by this job

Medical, dental, and vision benefits

Paid time off

401(k) savings plans

Health Savings Account (HSA)

Flexible Spending Accounts (FSAs)

Career development

Incentive bonus

Parental leave

Job summary

Caterpillar is seeking a Data Scientist I to support the Equipment Usage Analytics team in Chicago, onsite. You will build analytics to predict and measure application usage, downtime, and efficiency for a large fleet of connected assets using internal and external data.

You will develop analytics workflows, apply NLP and machine learning, and deliver business insights to management with visualization tools.

Qualifications

Degree in Applied Statistics, Data Science, or related field.
Experience with Python data analysis stacks (NumPy/SciPy/pandas).
Experience applying ML and statistical methods to business problems.
Ability to search, extract, and format data for analyses.

Responsibilities

Gather, mine, and process data at large scale.
Develop analytics workflows and ML models.
Apply NLP/text analysis to derive insights.
Present findings using data visualization tools.

Skills

Statistical tools

Machine learning

Python

Data management

Communication

Education

Bachelor's/Master's/PhD in Applied Statistics or Data Science

Tools

NumPy

SciPy

pandas

GitHub

Job description

Join Caterpillar’s Cat Digital organization as a Data Scientist I supporting the Equipment Usage Analytics team. The role focuses on building analytics to predict and measure application usage, downtime, and efficiency for a large fleet of connected assets using internal and external data.

Role Summary

You will develop analytics workflows and models that gather, mine, process, and analyze large-scale data volumes. The work includes applying Natural Language Processing, text analysis, and machine learning to produce business insights related to equipment usage and performance.

Key Responsibilities

Perform data gathering, data mining, and data processing at large scale, including creating appropriate data models.
Explore, promote, and implement semantic data capabilities using Natural Language Processing, text analysis, and machine learning techniques.
Define requirements and scope for data analyses, and present/report potential business insights to management using data visualization technologies.
Conduct research to improve data model optimization and algorithms for greater effectiveness and accuracy in analyses.

Required Qualifications

Working knowledge of statistical tools, processes, and practices to express business results in measurable scales, supporting business decision-making.
Working knowledge of machine learning principles, technologies, and algorithms, with the ability to develop, implement, and deliver related systems, products, and services.
Working knowledge of applying Python to solve business challenges, including using tools, techniques, and platforms to write and modify programming.
Working knowledge of data management systems, including the ability to use, support, and access facilities for searching, extracting, and formatting data for further use.
Typically holds a Bachelors, Masters, or PhD in Applied Statistics, Data Science, Business Analytics, Predictive Analytics, Business Intelligence & Analytics, Mathematics, Computer Science, Engineering (including Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural), or an equivalent technical degree.
Experience applying Python (including NumPy, SciPy, pandas, etc.) to solve business challenges.
Experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc. (typically 1+ years).
Working knowledge of cloud technologies such as AWS, Azure, or Google Cloud.
Advanced experience with version control and repositories such as GitHub.
Must demonstrate initiative, interpersonal skills, and the ability to communicate effectively.