Senior Data Scientist

Leírás

Career Area:

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.

Role Definition
Senior Data Scientist to design, develop, and deploy advanced AI/ML solutions that drive business impact. The ideal candidate will possess deep expertise in statistics, machine learning, large language models (LLMs), model evaluation, and Python-based solution development. This role will partner closely with product, engineering, and business stakeholders to develop scalable analytics and Generative AI solutions that improve decision-making, automation, and customer experiences.

Responsibilities
• Apply advanced statistical techniques to analyze large-scale structured and unstructured datasets, identify insights, and quantify business impact.
• Develop end-to-end ML and GenAI pipelines, including data preparation, model training, fine-tuning, evaluation, deployment, and monitoring.
• Build scalable Python-based solutions and reusable ML components that integrate with enterprise platforms and cloud environments.
• Collaborate with cross-functional teams to translate business problems into analytical solutions and communicate findings to technical and non-technical stakeholders.
• Stay current with emerging AI, machine learning, and LLM advancements, driving innovation and adoption of best practices.


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 Extensive Experience:
• Evaluates and makes contributions to best practices.
• Processes large quantities of detailed information with high levels of accuracy.
• Productively balances speed and accuracy.
• Employs techniques for motivating personnel to meet or exceed accuracy goals.
• Implements a variety of cross-checking approaches and mechanisms.
• Demonstrates expertise in quality assurance tools, techniques, and standards.

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 Working Knowledge:
• Completes specific tasks and initiatives utilizing machine learning technologies, such as search engine optimization.
• Utilizes specific tools and techniques to process descriptive and inferential statistics.
• Applies specific computing languages and tools in machine learning, such as R and Python.
• Explores to use machine learning in one own areas to make business improvements.
• Conducts data mining and cleaning initiatives.

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 Working Knowledge:
• Participates in the implementation and support of specialized programming languages.
• Conducts basic reviews on writing a specific programming language within a specific platform.
• Assists with the design and development of specialized programming languages.
• Follows an organization's standards, policies and guidelines for structured programming specifications.
• Diagnoses and reports minor or routine programming language problems.

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 Extensive Experience:
• Writes, debugs and implements complex queries involving multiple tables or databases.
• Works with aggregate functions, complex joins, groupings, dynamic and embedded SQL's (Structured Query Languages).
• Teaches others about query optimization techniques and facilities.
• Consults on query optimization, interactive queries, testing and verification.
• Evaluates all major database access tools and functions for distributed databases.
• Compares and contrasts the benefits and drawbacks of various SQL products.

Requirements Analysis: 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.
Level Working Knowledge:
• Follows policies, practices and standards for determining functional and informational requirements.
• Confirms deliverables associated with requirements analysis.
• Communicates with customers and users to elicit and gather client requirements.
• Participates in the preparation of detailed documentation and requirements.
• Utilizes specific organizational methods, tools and techniques for requirements analysis.

Posting Dates:

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

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