Role Overview
The Digital Operations Engineer will apply statistical analysis, machine learning, and data science methods to solve business problems across operational, financial, and strategic domains. They will leverage enterprise data platforms to prepare, transform, and model datasets for analytics, reporting, and AI-driven applications.
What You Will Do
Responsibilities include applying statistical analysis, machine learning, and data science methods, leveraging enterprise data platforms, supporting AI-enabled workflows, developing and maintaining dashboards, reports, and analytical models, collaborating with cross-functional teams, and supporting the enterprise data foundation.
Why It Might Be a Fit
The ideal candidate will have a strong foundation in statistics, machine learning, and quantitative analysis methods, with proficiency in Python and SQL for data analysis, modeling, and automation.
Requirements
- Master’s degree in Business Analytics, Statistics, Computer Science, Mathematics, Data Science, Engineering, or a closely related field
- Strong foundation in statistics, machine learning, and quantitative analysis methods
- Proficiency in Python and SQL for data analysis, modeling, and automation
- Knowledge of data warehousing concepts, ETL processes, and cloud-based data platforms
- Familiarity with machine learning techniques including classification, regression, clustering, and forecasting
- Understanding of artificial intelligence concepts including natural language processing, large language models, and retrieval-augmented generation
- Strong analytical and problem-solving skills
- Excellent communication skills
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short-term disability insurance
- Long-term disability insurance
- Paid time off
To apply for this job please visit job-boards.greenhouse.io.
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