ML Architect/ Data Scientist (Inventory Forecasting) - R01563519

About Brillio: Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year. Architect Know what it’s like to work and grow at Brillio: Click here country: US all locations: [Dallas, Texas, United States] commitment: Third Party Contract department: AI & Data Engineering location: Dallas, Texas, United States team: AI & Data Engineering : Data Science Primary Skills: Azure API Management, Solution Architecture - Azure, Azure DevOps, Azure Storage Queues, Azure PaaS Services, Azure Networking, Azure Logic Apps, Azure Content Delivery Network, Azure App Service, Azure SQL, Azure AD, Azure Virtual Machines Specialization: Azure Architecture: Architect Job requirements: Job Title: Machine Learning Engineer / Data Scientist (Inventory Forecasting) Location: Florida (FL)  Job Summary:We are seeking a skilled Machine Learning Engineer / Data Scientist with strong experience in classical machine learning techniques and inventory forecasting. The ideal candidate will have hands-on expertise in time series modeling and a good understanding of modern cloud-based ML platforms, particularly Azure AutoML. Experience working with or building agentic (AI-driven autonomous or semi-autonomous) solutions is highly desirable. Key Responsibilities: Develop and implement forecasting models for inventory and demand planning using classical time series techniques such as ARIMA, SARIMA, and related methods. Analyze large datasets to identify trends, seasonality, and patterns impacting inventory and supply chain performance. Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services. Design and implement scalable, production-ready ML solutions in a cloud environment. Collaborate with cross-functional teams including business stakeholders, data engineers, and product teams to deliver actionable insights. Explore and contribute to agentic AI solutions, including automation and intelligent decision-making systems. Monitor model performance and continuously improve accuracy and efficiency. Required Skills & Qualifications: Strong experience in classical machine learning and time series forecasting (ARIMA, SARIMA, etc.). Solid understanding of inventory forecasting, demand planning, or supply chain analytics. Hands-on experience with Azure AutoML and Azure ML ecosystem. Proficiency in Python and common ML libraries (e.g., pandas, scikit-learn, statsmodels). Experience with data preprocessing, feature engineering, and model evaluation. Knowledge of deploying ML models in production environments. Preferred Qualifications: Experience in building or working with agentic/AI-driven autonomous systems. Familiarity with MLOps practices and CI/CD pipelines. Experience with big data technologies and distributed computing frameworks. Strong problem-solving skills and ability to work in a collaborative environment. Work Model: Hybrid work setup based in Florida (FL). Nice to Have: Experience in retail, e-commerce, or supply chain domains. Exposure to advanced forecasting techniques or deep learning-based time series models. #LSR1