
Data Analytics Specialist
- Chicago, IL
- Permanent
- Full-time
- Identify and develop advanced analytics use cases to resolve complex technical challenges, optimize processes, enhance revenue, ensure environmental sustainability, and improve safety.
- Drive ideas from conception to production using best-in-class Machine Learning Operations (MLOps) and Development Operations (DevOps) practices.
- Develop and optimize Machine Learning (ML) models and pipelines, ensuring their efficient deployment, monitoring, and scaling.
- Explore diverse data sources to improve predictive modeling and optimize business strategies.
- Assess Artificial Intelligence (AI) tools and methods for data analysis, enhancing business impact and decision-making.
- Implement predictive modeling techniques to optimize production facilities, revenue streams, and operational efficiencies.
- Generate documentation in line with established standards to support the development and deployment process.
- Collaborate with cross-functional teams, including IT, engineering, and business stakeholders, to drive data-driven solutions.
- Contribute to technical task forces investigating incidents and solving domain-specific problems using AI/ML techniques.
- Publish research papers for peer-reviewed journals and presents findings to other organizations and conferences to advance industry knowledge.
- Promotes a learning environment through knowledge-sharing, and fosters a culture of continuous learning and innovation.
- Provide leadership and mentorship to junior team members and specialists.
- Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering with a background in Engineering is highly preferred.
- 20 years of overall experience, with hands-on experience in Data Science, Natural Language Processing (NLP), Computer Vision, and/or ML projects in the industry.
- Expertise in MLOps, DevOps, AIOps, DataOps and related operational frameworks for model deployment, monitoring, and automation.
- Experience in data collection, cleaning, preprocessing, and wrangling for industry-related problems based on domain knowledge.
- Proficiency in Platforms such as Python, R, SQL, SAS, Scala, and cloud platforms such as Azure and Google Cloud (Vertex AI).
- Expertise in visualization tools and packages; User Interface (UI) experience with Power Business Intelligence (Power BI) or similar tools.
- Experience with IT architecture and deploying models in on-prem environments.
- Strong understanding of continuous integration / continuous deployment (CI/CD) pipelines, containerization (Docker, Kubernetes), and automation frameworks.
- Demonstrated ability to publish research or contribute to industry knowledge through journal papers, conference proceedings, or whitepapers.