Senior Data Scientist — AI/ML for Enterprise Analytics

Insight Global; Wood Dale (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

Insight Global is seeking a Machine Learning Data Scientist to design, develop, and scale analytics and ML solutions across ERP systems and distribution channels. You will apply statistical modeling, predictive analytics, and AI/ML techniques to uncover insights, improve forecasting, and drive operational efficiency.

The ideal candidate has a strong technical background and can communicate complex findings to non-technical stakeholders while collaborating with cross-functional teams and business

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Engineering, CS or related quantitative field; Master’s preferred.
• 6+ years of experience in data science, ML, or analytics.
• Strong background in statistical modeling, forecasting, and experimental design.
• Experience building, deploying, and improving predictive ML models.
• Proficiency in Python and/or SQL for data analysis and modeling.
• Experience with Azure, AWS, GCP, Spark or distributed data platforms.
• Excellent communication to explain concepts to non‑technical stakeholders.
• Knowledge of data integration across multiple enterprise systems.
• Experience in aviation, supply chain, logistics, or related industries is a plus.
• Experience in government-regulated environments is a plus.

Skills

Statistical modeling

Forecasting

Regression

Classification

Clustering

Experimental design

Python

SQL

Large datasets

Communication

Azure

AWS

GCP

Spark

Distributed processing

Analytics products

Data integration

Education

Bachelor’s degree

Master’s degree preferred

Tools

Azure

AWS

GCP

Spark

Job description

Insight Global is seeking a Machine Learning Data Scientist to design, develop, and scale analytics and ML solutions across ERP systems and distribution channels. You will apply statistical modeling, predictive analytics, and AI/ML techniques to uncover insights, improve forecasting, and drive operational efficiency.

The ideal candidate has a strong technical background and can communicate complex findings to non-technical stakeholders while collaborating with cross-functional teams and business