Scientist 2, Data Science

Role Overview

The Data Science team within our Operations function builds analytics and machine learning solutions that develop advanced analytics tools and machine learning models to solve complex business problems using mathematics, statistics, and machine learning methods, and take ideas from concept through data preparation, model building, application development, and system integration. You will work hands-on across advanced analytics and machine learning model development, data preparation, and application development, using tools and environments including Python, GitHub, Linux, Docker, and machine learning algorithms.

Essential Duties and Responsibilities

• Automate data extraction, cleaning, processing, feature engineering, and exploratory analysis using Python, R, and SQL across structured and unstructured operational datasets.
• Develop advanced machine learning and deep learning models to support operational excellence, predict outcomes of interest, and identify patterns across enterprise datasets
• Build and deploy end-to-end analytics applications, covering data preparation, model development, and system integration
• Visualize analytical findings and model outputs using enterprise BI tools such as Tableau, Power BI, or similar platforms to create intelligent dashboards that support operational decision-making.
• Validate and monitor deployed models in production, tracking performance drift and retraining as needed to maintain accuracy and reliability.
• Document model methodologies, data pipelines, and application architecture using version-controlled repositories to support reproducibility and team collaboration.
• Translate analytical findings into clear, actionable insights and present results to engineering and operations partners across functions.
• Leverage AI-assisted tools to accelerate workflows, while critically evaluating outputs before use.

Function: Engineering
Experience Level: Entry Level