Data Scientist - Job Opportunity at Caterpillar Inc.

Chillicothe, United States
Full-time
Mid-level
Posted: March 18, 2025
Hybrid
USD 101,546 - 155,400 per year

Benefits

Comprehensive healthcare package including medical, dental, and vision with HSA option - above industry standard
401(k) savings plan with company matching
Flexible work arrangement with 40% remote option - competitive for manufacturing sector
Progressive parental leave and adoption benefits
Extensive professional development through tuition reimbursement
Performance-based incentive bonus structure
Comprehensive wellness programs including health lifestyle initiatives
Multiple insurance coverages including life and disability
Flexible spending accounts for additional tax advantages
Generous PTO including vacation, holidays and volunteer time

Key Responsibilities

Lead complex data analysis initiatives to drive strategic business decisions in manufacturing operations
Direct end-to-end data processing and model development for large-scale industrial applications
Implement advanced NLP and machine learning solutions for semantic data analysis
Develop and optimize statistical models for production quality improvement
Create visualization solutions using Power BI for executive decision support
Lead requirements gathering and scope definition for enterprise-wide analytics projects
Conduct research on model optimization to enhance analytical accuracy
Support full BI lifecycle from design through maintenance
Develop proactive risk detection systems for quality control

Requirements

Education

Master's degree in Industrial and Systems Engineering, Computer Engineering, or related field

Experience

2.5 years as Data Analyst, Quality Analyst, or related role

Required Skills

Data management systems for product development R and Python for machine learning Data visualization and query tools SQL database management Statistical analysis using Minitab Machine learning and AI algorithms Product Development Data Lake management Agile methodology Natural Language Processing Power BI
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Sauge AI Market Intelligence

Industry Trends

Manufacturing sector is increasingly leveraging AI and ML for quality control and process optimization, creating high demand for data scientists with industrial expertise Integration of IoT and real-time analytics in manufacturing operations is driving need for professionals who can bridge data science with industrial engineering Growing emphasis on predictive maintenance and quality control systems is creating specialized roles for data scientists in manufacturing

Salary Evaluation

The offered salary range is competitive for the midwest region and aligns with industry standards for mid-level data scientists in manufacturing. The range allows for growth based on experience and specialized skills.

Role Significance

Likely part of a 5-8 person data science team within a larger digital transformation department, typical for enterprise-level manufacturing organizations
Mid-level position with significant project ownership and technical leadership responsibilities. The role involves both hands-on technical work and strategic decision-making.

Key Projects

Quality control optimization using advanced analytics Predictive maintenance system development Process efficiency improvement through ML applications Enterprise-wide BI dashboard development Cost optimization through data-driven decision making

Success Factors

Strong background in both data science and manufacturing processes Ability to translate complex technical concepts to business stakeholders Experience with large-scale industrial data systems Strong project management and stakeholder communication skills Deep understanding of quality control processes and metrics

Market Demand

Very high demand, particularly for data scientists with manufacturing sector experience and quality control expertise. The combination of traditional manufacturing knowledge with modern data science skills is relatively rare.

Important Skills

Critical Skills

Manufacturing process knowledge combined with data science expertise Advanced statistical analysis and modeling skills Strong programming capabilities in Python and R Experience with industrial data systems and quality control processes

Beneficial Skills

Knowledge of IoT and sensor data analysis Experience with cloud computing platforms Understanding of regulatory compliance in manufacturing Expertise in specific manufacturing quality standards

Unique Aspects

Rare opportunity to apply data science in heavy manufacturing context
Significant focus on quality control and process optimization
Balance of technical work with business impact
Strong emphasis on professional development and career growth

Career Growth

Typical progression to senior role in 2-3 years, management track possible in 3-4 years with demonstrated leadership capabilities

Potential Next Roles

Senior Data Scientist Lead Data Scientist Analytics Manager Digital Transformation Lead Technical Product Manager

Company Overview

Caterpillar Inc.

Caterpillar is a global leader in construction and mining equipment manufacturing, with a strong focus on digital transformation and data-driven operations

Fortune 100 company with dominant market position in heavy equipment manufacturing and increasing investment in digital capabilities
The Chillicothe location is significant for R&D and digital initiatives, with strong connection to corporate headquarters
Professional environment with emphasis on innovation and continuous improvement, balanced with traditional manufacturing values
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