EPITEC
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist I with a contract length of "unknown," offering a pay rate of "unknown," located in "unknown." Key skills include Python, Power BI, SQL, and machine learning techniques. A background in heavy equipment industries is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
288
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🗓️ - Date
October 4, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Peoria, IL
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🧠 - Skills detailed
#Cloud #Python #Mathematics #Visualization #Azure #SQL (Structured Query Language) #Project Management #Computer Science #Data Analysis #Clustering #Snowflake #Statistics #Neural Networks #Microsoft Power BI #AWS (Amazon Web Services) #Regression #Forecasting #Logistic Regression #Data Science #ML (Machine Learning) #BI (Business Intelligence)
Role description
About the Role:
A leading industrial equipment company is seeking a talented and motivated Data Scientist I to join its Machine Data Insights team within the Machine Analytics division. This team is dedicated to uncovering actionable insights from machine usage data to improve customer productivity, safety, and strategic decision-making across product development, aftermarket services, and demand forecasting.
This is a unique opportunity to contribute to high-impact analytics projects that shape the future of industrial operations and customer engagement. You’ll work in a collaborative environment with cross-functional teams, applying advanced statistical and machine learning techniques to real-world challenges.
Key Responsibilities:
• Collaborate on cross-functional project teams to solve business problems using data-driven approaches.
• Collect, analyze, and interpret machine data to uncover usage patterns and operational insights.
• Develop, validate, and refine statistical models and machine learning algorithms.
• Create and maintain Power BI dashboards to communicate key metrics such as inventory levels and rebuilds.
• Support strategic initiatives by analyzing work order data and competitive landscapes.
• Apply digital technologies to enhance model inputs and outputs.
• Contribute independently while learning company processes, products, and organizational structure.
Required Qualifications:
• Bachelor’s degree in Engineering, Computer Science, Statistics, Economics, Mathematics, or a related quantitative field.
• 1–2 years of professional experience in data analysis or a Master’s/PhD degree.
• Proficiency in statistical and data visualization tools (e.g., Python, Power BI, SQL, Excel).
• Strong initiative, interpersonal skills, and communication abilities.
Preferred Qualifications:
• Advanced degree in Data Science, Applied Statistics, Business Analytics, Engineering, or related technical field.
• Experience with statistical methods (regression, hypothesis testing, ANOVA, etc.).
• Familiarity with machine learning techniques (Clustering, Logistic Regression, Random Forests, SVM, Neural Networks).
• Background in heavy equipment industries (automotive, aerospace, mining, etc.).
• Experience with cloud platforms (AWS, Azure, Google Cloud).
• Knowledge of Snowflake, LENs data, and Caterpillar work order structures.
• Dealer Service Operations experience is a plus.
Soft Skills:
• Strategic thinking and customer-centric mindset.
• Strong collaboration and relationship-building skills.
• Ability to anticipate and address customer needs to drive business growth.
Why This Role?
This position offers exposure to cutting-edge analytics, cross-functional collaboration, and continuous learning. You’ll develop advanced problem-solving and project management skills while working with industry-leading tools and technologies. It’s a chance to grow professionally in a supportive and innovative environment.
About the Role:
A leading industrial equipment company is seeking a talented and motivated Data Scientist I to join its Machine Data Insights team within the Machine Analytics division. This team is dedicated to uncovering actionable insights from machine usage data to improve customer productivity, safety, and strategic decision-making across product development, aftermarket services, and demand forecasting.
This is a unique opportunity to contribute to high-impact analytics projects that shape the future of industrial operations and customer engagement. You’ll work in a collaborative environment with cross-functional teams, applying advanced statistical and machine learning techniques to real-world challenges.
Key Responsibilities:
• Collaborate on cross-functional project teams to solve business problems using data-driven approaches.
• Collect, analyze, and interpret machine data to uncover usage patterns and operational insights.
• Develop, validate, and refine statistical models and machine learning algorithms.
• Create and maintain Power BI dashboards to communicate key metrics such as inventory levels and rebuilds.
• Support strategic initiatives by analyzing work order data and competitive landscapes.
• Apply digital technologies to enhance model inputs and outputs.
• Contribute independently while learning company processes, products, and organizational structure.
Required Qualifications:
• Bachelor’s degree in Engineering, Computer Science, Statistics, Economics, Mathematics, or a related quantitative field.
• 1–2 years of professional experience in data analysis or a Master’s/PhD degree.
• Proficiency in statistical and data visualization tools (e.g., Python, Power BI, SQL, Excel).
• Strong initiative, interpersonal skills, and communication abilities.
Preferred Qualifications:
• Advanced degree in Data Science, Applied Statistics, Business Analytics, Engineering, or related technical field.
• Experience with statistical methods (regression, hypothesis testing, ANOVA, etc.).
• Familiarity with machine learning techniques (Clustering, Logistic Regression, Random Forests, SVM, Neural Networks).
• Background in heavy equipment industries (automotive, aerospace, mining, etc.).
• Experience with cloud platforms (AWS, Azure, Google Cloud).
• Knowledge of Snowflake, LENs data, and Caterpillar work order structures.
• Dealer Service Operations experience is a plus.
Soft Skills:
• Strategic thinking and customer-centric mindset.
• Strong collaboration and relationship-building skills.
• Ability to anticipate and address customer needs to drive business growth.
Why This Role?
This position offers exposure to cutting-edge analytics, cross-functional collaboration, and continuous learning. You’ll develop advanced problem-solving and project management skills while working with industry-leading tools and technologies. It’s a chance to grow professionally in a supportive and innovative environment.
