Infor

The Infor Decision Analytics and Science (IDEAS) team shapes Infor’s AI/ML strategy by driving development across industry-specific Augmented Intelligence solutions. These solutions, spanning Asset, Forecast, Customer, Pricing, People, Inventory, and Operational Intelligence domains, empower enterprise customers with rapid and measurable results. Our mission is to advance purpose-built Machine Learning (ML) and Optimization engines. To support this mission, IDEAS seeks a Senior Scientist with deep expertise in applied ML and industry experience to lead the charge in delivering robust, scalable, and user-centric algorithmic solutions. In this pivotal role, your contributions will shape highly automated, explainable, and reusable ML solutions that can be rapidly deployed and managed at a scale for enterprise needs.

A Day in The Life Typically Includes:

• Design, develop, test, and deploy scalable ML models, including time series forecasting, anomaly detection, clustering, classification, regression, recommendation, and semantic search.
• 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.

Required skills:

• Experience in developing and implementing advanced ML models in real-world settings.
• Development experience in Python, PySpark, Neo4j, SQL, and scientific libraries for statistical analysis and ML.
• Relevant experience in explainable AI (XAI), AutoML, GraphML and MLOps.
• Skilled in data modeling and handling large datasets, with experience in data visualization tools such as Tableau, Power BI, or similar.
• Experience using JIRA for task management and collaboration.