Design, develop, and maintain advanced analytical models, including machine learning and statistical approaches, to support digital products and enterprise initiatives.
Analyze large, complex datasets to identify trends, patterns, and opportunities for improvement.
Partner with cross‑functional teams to define analytical requirements and translate business questions into data science solutions.
Support data quality initiatives by validating data sources, identifying gaps, and recommending improvements.
Communicate insights and model results clearly to technical and non‑technical stakeholders.
Contribute to continuous improvement of analytics tools, methodologies, and best practices within Cat Digital.
Requirements
Typically, a Bachelors, Masters, or PhD degree in Applied Statistics, Data Science, Business Analytics, Predictive Analytics, Business Intelligence & Analytics, Mathematics, Computer Science, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), or equivalent technical degree.
Extensive hands‑on experience: applying Python programming to solve business challenges.
Advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc.
Practical applications of Machine Learning techniques such as Clustering, Logistic Regression, Random Forests, SVM or Neural Networks.
Working with generative AI, with an understanding of strengths, limitations, and responsible use considerations.
Advanced experience in quantifying the costs, benefits, risks and chances for success before recommending a course of action.
In‑depth technical and problem‑solving skills and evidence of continuous learning in the analytics field.
Working knowledge with cloud technologies (AWS, Azure, Google Cloud, etc.).
Advanced experience with version control / repositories such as GitHub.
Experience operating in an Agile environment.
Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.