Caterpillar Recruitment Program 2026 | Hiring Data Scientist – Data Analytics

Qualifications

Skill Descriptors:

• Business Statistics: 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.

Level Working Knowledge:

• • Explains the basic decision process associated with specific statistics.
• • Works with basic statistical functions on a spreadsheet or a calculator.
• • Explains reasons for common statistical errors, misinterpretations, and misrepresentations.
• • Describes characteristics of sample size, normal distributions, and standard deviation.
• • Generates and interprets basic statistical data.

Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.

Level Working Knowledge:

• • Accurately gauges the impact and cost of errors, omissions, and oversights.
• • Utilizes specific approaches and tools for checking and cross-checking outputs.
• • Processes limited amounts of detailed information with good accuracy.
• • Learns from mistakes and applies lessons learned.
• • Develops and uses checklists to ensure that information goes out error-free.

Analytical Thinking: 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.

Level Working Knowledge:

• • Approaches a situation or problem by defining the problem or issue and determining its significance.
• • Makes a systematic comparison of two or more alternative solutions.
• • Uses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns.
• • Identifies the major forces, events and people impacting and impacted by the situation at hand.
• • Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.

Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.

Level Basic Understanding:

• • Explains the definition and objectives of machine learning.
• • Describes the algorithms and logic of machine learning.
• • Distinguishes between machine learning and deep learning.
• • Gives several examples on the implementation of machine learning.

Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.

Level Basic Understanding:

• • Describes the basic concepts of programming and program construction activities.
• • Uses programming documentation including program specifications in order to maintain standards.
• • Describes the capabilities of major programming languages.
• • Identifies locally relevant programming tools.

Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.

Level Working Knowledge:

• • Defines, creates and tests simple queries by using associated command language in a specific environment.
• • Applies appropriate query tools used to connect to the data warehouse.
• • Obtains and analyzes query access path information and query results.
• • Employs tested query statements to retrieve, insert, update and delete information.
• • Works with advanced features and functions including sorting, filtering and making simple calculations.