Infor

The Infor Decision Analytics and Science (IDEAS) team is responsible for setting the AI/ML strategy at Infor. Our industry-specific Augmented Intelligence (AI) solutions suite in Asset, Forecast, Customer, Pricing, People, Inventory and Operational Intelligence domains provides rapid and measurable value to enterprise customers. All our solutions are powered by purpose-built ML and Optimization engines. In pursuit of advancing our ML Engines, IDEAS is currently seeking a Senior Scientist. This pivotal role requires both industry experience and technical expertise in building real-world ML models for enterprise applications. Your contributions will be instrumental in crafting highly automated, robust, reusable, explainable, user-friendly, and self-serviced algorithmic solutions that can be swiftly deployed and managed at scale.

A Day in The Life Typically Includes:

· Design, develop, test, deploy, monitor, and improve ML models for time series, anomaly detection, clustering, classification, regression, recommendation, and semantic search engines.

· Develop quality code in Python adhering to common software development processes such as unit and functional testing, version control, code reviews, CI/CD, and documentation.

· Build expertise to package and deploy ML engines and augmented intelligence solutions using Infor OS.

· Extract, process, cleanse, model, and conduct an in-depth evaluation of enterprise datasets to extract actionable insights that provide value to our customers.

· Design, execute, analyze, and interpret experiments and investigations.

· Navigate ambiguous or incomplete business problems and guide the process of formulating them into clear functional and technical requirements for improving enterprise outcomes.

· Communicate complex technical concepts and insights to non-technical stakeholders through presentations, reports, and dashboards.

Basic Qualifications:

· Prior industry experience in developing and implementing advanced ML models.

· Familiarity with explainable AI (XAI), AutoML, and MLOps.

· Software development experience in Python, PySpark, and SQL and familiarity with scientific libraries commonly used in statistical analysis and machine learning.

· Familiarity with software development environments such as VSCode, and version control using Git and CI/CD pipelines.

· Knowledge of data models and relational databases. Proficiency in handling large datasets and data analysis with Tableau, Power BI, or similar BI tools.

· Familiarity with task management with JIRA.

Preferred Qualifications:

· PhD or Master’s in Statistics, Mathematics, Physics, Computer Science, Operations Research, or a related quantitative discipline from an accredited university.

· Experience in system design, batch, and real-time architectures.

· Familiarity with Infor and other ERPs across different industry segments.

· Ability to independently learn new techniques in ML relevant to enterprise applications.