Seeking a highly skilled and innovative Senior Data Scientist to join our analytics team. In this role, you will bridge the gap between complex data engineering and advanced predictive modeling. You will leverage business intelligence, machine learning, and AI to extract actionable insights from diverse datasets, playing a pivotal role in developing scalable models and deploying AI solutions that drive strategic decision-making across the organization.

 
 
location: Warrenville, Illinois
job type: Permanent
salary: $130,000 - 150,000 per year
work hours: 9am to 5pm
education: Bachelors
 
responsibilities:
Architecture & ETL: Design, optimize, and maintain robust ETL processes for data ingestion and storage. Architect databases using best practices to ensure long-term data integrity and accessibility.

Modeling & AI Deployment: Build, train, and deploy machine learning models into production environments using cloud-based best practices.

Advanced Analytics: Conduct deep-dive data mining and exploratory analysis (EDA) to identify patterns, trends, and anomalies.

Cross-Functional Collaboration: Partner with business units to translate complex requirements into technical analytical solutions.

Visualization: Support the development of high-impact dashboards and visualization tools (Power BI/Tableau) for executive stakeholder reporting.

Innovation: Stay at the forefront of emerging AI/ML trends, specifically in NLP and linked data integration, to continuously evolve our modeling approaches.

 
qualifications:
Education: Bachelor's degree in Computer Science, Data Science, or a related technical field.

Experience: 5+ years of professional experience in a Data Scientist or Data Engineer role.

Programming: Mastery of SQL, Python, and Java.

Azure Ecosystem: In-depth, hands-on experience with Azure Data Factory, Azure Databricks, and Azure Service Bus.

Database Management: Strong command of Microsoft SQL Server, including structured (SQL) and unstructured (NoSQL) data environments.

Machine Learning: Deep knowledge of ML frameworks, model training, and cloud deployment. Proficiency in Natural Language Processing (NLP) is highly preferred.