Senior Data Scientist

Caterpillar; Nuevo Laredo; On-site; MXN 600,000 - 1,000,000; Full time

Job summary

Caterpillar is seeking a data science and analytics professional to lead development of advanced analytics, ML, and AI-powered solutions for the Reman division in Mexico. You will build models with Python, deploy solutions, and collaborate across business stakeholders to translate needs into scalable data products.

The role emphasizes governance, reproducible pipelines, and actionable BI, with strong focus on delivering measurable business value and sustainable analytics practices.

Qualifications

• Bachelor's degree in Engineering, Computer Science, or other technical field, or proven work experience.
• Hands-on experience building data science and ML solutions in Python.
• Ability to translate business problems into data science approaches.
• Experience with modern analytics tools and deployment.
• Strong communication of technical insights to non-technical stakeholders.

Responsibilities

• Lead design, development, and deployment of analytics, ML, and AI-enabled solutions across Reman Division.
• Apply statistical modeling, ML, optimization, forecasting, and simulation to drive business value.
• Develop, validate, and operationalize analytics and predictive models using Python and modern practices.
• Build analytics products that combine ML outputs, data assets, and Power BI reporting.
• Collaborate with stakeholders to frame problems and translate requirements into data solutions.
• Research and prototype emerging AI approaches, including generative AI and automation.
• Use Python, Kedro, dbt, Docker, AWS, Snowflake, Azure DevOps to create repeatable workflows.
• Ensure data pipelines, semantic models, and governed data products support scalable solutions.
• Promote best practices: source control, testing, experiment tracking, model docs, deployment standards.
• Lead Agile planning and design reviews; mentor team on data science practices.
• Champion sustainable analytics product development and reduce technical debt.
• Define standards for model documentation and monitoring.

Skills

Python

ML model development

Data analysis

Communicate insights

Education

Bachelor's degree in Engineering, Computer Science, or technical field

Tools

Kedro

dbt

Docker

AWS

Snowflake

Azure DevOps

Git

Power BI

Job description

Career Area: Technology, Digital and Data

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.

CATERPILLAR REMANUFACTURING

Do you have a passion for helping customers and supporting a sustainable solution? Since 1973, Cat Reman has helped bring the value at the core of every Cat product back to life. Customers look to us to provide a high-quality solution that is good for their business - and promotes sustainability. It's important to us to deliver. Our team is full of industry leaders. Together, following common values, we share a passion for delivering sustainability benefits that help the company contribute to a circular economy. It’s rewarding to work, with an inspiring team, where every contribution matters.

Degree Requirement

Bachelor’s degree in Engineering, Computer Science, or other Technical field; or proven work experience

What You Will Do

• Lead the design, development, and deployment of advanced analytics, machine learning, and AI-enabled solutions that solve complex business problems across the Reman Division.
• Apply statistical modeling, machine learning techniques, optimization methods, forecasting, simulation, and experimentation to identify opportunities, improve decisions, and deliver measurable business value.
• Develop, validate, and operationalize descriptive analytics and predictive models using Python and modern data science practices while ensuring solutions are explainable, maintainable, and aligned to business objectives.
• Build analytics products and decision-support tools that combine machine learning outputs, curated data assets, and intuitive Power BI reporting to improve adoption and business actionability.
• Partner with business stakeholders to frame analytical problems, define success measures, translate business requirements into data science solutions, and communicate insights to technical and non-technical audiences.
• Research, prototype, and implement emerging AI development approaches, including generative AI, intelligent agents, natural language interfaces, and automation opportunities that improve business processes and analytical productivity.
• Use python, Kedro, dbt, Docker, AWS, Snowflake, Azure DevOps, and related tools to create repeatable, governed, and production-ready analytical workflows that support model development, deployment, and monitoring.
• Collaborate with data engineering and platform partners to ensure required data pipelines, semantic models, data quality frameworks, and governed data products are available to support scalable analytical solutions.
• Establish and promote data science best practices including source control, code review, automated testing, experiment tracking, model documentation, reproducible pipelines, and deployment standards.
• Lead Agile planning, analytical design reviews, model review discussions, and project execution efforts while mentoring team members on data science, machine learning, AI development, and analytics engineering practices.
• Champion sustainable analytical product development by reducing technical debt, improving reusability, and promoting standardized approaches across the Reman Analytics organization.
• Define and execute standards for model documentation, metadata management, knowledge sharing, monitoring, and operational supportability to improve long-term maintainability of analytical solutions.

Top Candidates Will Have

• Hands-on experience developing data science and machine learning solutions using Python, including model development, validation, deployment, monitoring, and continuous improvement.
• Strong understanding of supervised and unsupervised learning, forecasting, optimization, statistical analysis, feature engineering, model evaluation, and practical application of ML techniques to business problems.
• Experience building AI-enabled solutions, including generative AI applications, natural language solutions, intelligent agents, or automation tools that improve analytical workflows and business decision-making.
• Practical experience with modern analytics and development tools such as dbt, Kedro, AWS, Docker, Snowflake, Azure DevOps, Git, and Power BI.
• Ability to translate ambiguous business needs into structured analytical approaches, communicate insights clearly, and deliver solutions that are adopted and sustained by the business.
• Working knowledge of data engineering concepts, ELT/ETL patterns, data modeling, and data quality practices needed to support reliable analytical and machine learning solutions.

What You Will Have

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.

Visa sponsorship is NOT available for this position. Domestic relocation assistance is offered for this position.

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

About Caterpillar Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. For 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed.

There’s more to work at Caterpillar than just the work itself. We hire smart, friendly people and it shows in our culture. We hold ourselves to high standards and make sure our values of integrity, excellence, teamwork, commitment and sustainability come to life in the way we work. We make sure our employees feel continuously challenged while also supported. We provide professional growth opportunities, including leadership programs. We celebrate the diversity of our team, while also working together as one Caterpillar. Our culture, like everything at our company, is made possible by each employee’s contribution. Person by person, we create the environment we work in, and we are proud of the Caterpillar we’ve built.