td>| Duties: | Responsible for the exploration, aggregation, transformation, and cleansing of vehicle data across a variety of disparate sources and platforms, ensuring data integrity and consistency at scale; design, implement, and continuously optimize advanced predictive machine learning models to drive accurate and actionable business forecasts, leveraging complex datasets; architect, develop, and maintain high-performance APIs in Python, ensuring seamless integration with diverse data ecosystems while adhering to best practices for scalability and security; support efforts to streamline and automate the data pipeline, encompassing data acquisition, feature engineering, model development, and deployment workflows, optimizing for performance, efficiency, and scalability; coordinate and execute complex ad-hoc data analysis tasks, providing rapid, data-driven insights for immediate business needs; provide mission-critical on-call support to ensure the continued operation of business production systems, troubleshooting and resolving issues with minimal impact to operations; utilize and apply knowledge of Python, SQL, Scikit-learn, XGBoost, Prophet, ARIMA, RESTful APIs, GCP, Terraform, Docker, VBA, and ODBC to complete assignments; translate complex analytical findings into clear, actionable insights; utilize cutting-edge Natural Language Processing (NLP) techniques to extract valuable insights from large volumes of unstructured text data, integrating AI-driven solutions to deliver sophisticated data analysis that directly impacts automotive operations and strategic initiatives; apply advanced statistical methodologies including Regression Analysis, Bayesian Inference, and machine learning-based forecasting techniques, to model and predict complex variables like market incentives, inventory management, sales forecasting, and operational performance; provide data-driven insights to optimize production strategies and facilitate high-level decision-making; leverage Cloud Computing platforms (primarily GCP) to architect and scale infrastructure for processing, storing, and analyzing massive automotive datasets; deploy data science solutions that integrate seamlessly with manufacturing and operational environments to drive efficiency, accuracy, and business intelligence; and present models and results to stakeholders, including business executives, to influence strategic decision-making. Education: Master’s – Data Science, Computer Science, Computer Engineering, Systems Engineering, or in a related field of study (will accept equivalent foreign degree); Training: None; Experience: One (1) year in the position above, as a Data Analyst, Data Engineer, as a Data Engineering Specialist, or in a related occupation; Other Requirements: Experience must include one (1) year use of all the following: Python, SQL, Scikit-learn, XGBoost, Prophet, ARIMA, RESTful APIs, GCP, Terraform, Docker, VBA, and ODBC.You will partner closely with senior leadership, architects, data science, analytics, IT, and business stakeholders to design resilient, scalable, and trusted data systems that support real-time decisioning, advanced analytics, and AI/ML applications. THE DAY-TO-DAY: Define the multi-year architectural vision for MGM's Lakehouse platform, including compute, storage, orchestration, semantic layers, governance, and reliability. As the architectural owner of domain-wide data models and certified datasets, you will drive metric consistency, platform scalability, and business-aligned data solutions in close partnership with Data Science, Analytics, IT, and commercial leadership. THE JOB: We are seeking a Staff Commercial Data Engineer to architect and elevate the Marketing and Revenue Management data platforms that power commercial decision-making across Gaming, Hospitality, Loyalty, and Marketing. p>You will be responsible for designing, developing, testing, and deploying data services that interact with large-scale data systems, while also supporting production processes and operational excellence. In this role, you will collaborate with developers, architects, product managers, and feature teams to deliver core platform components that support scalable, secure, and high-performing web services. This role emphasizes end-to-end backend solution development, cloud-native architecture, and operational deployment using AWS services such as Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, SageMaker, etc. Job Description:Under limited supervision, the AI Engineer is responsible for designing, developing, and deploying production-ready AI and machine learning solutions that address complex business needs. This role emphasizes end-to-end backend solution development, cloud-native architecture, and operational deployment using AWS services such as Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, SageMaker, etc. Responsibilities:Under limited supervision, the AI Engineer is responsible for designing, developing, and deploying production-ready AI and machine learning solutions that address complex business needs. p> Azure Databricks Data Architect in manufacturing, with strong Databricks/Azure engineering depth plus architecture and governance skills, backed by Azure and Databricks credentials. Deep Databricks platform expertise: notebooks, jobs/workflows, cluster configuration, Databricks SQL, and applying Medallion (Bronze/Silver/Gold) architecture patterns. Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment. - Communicate complex technical concepts clearly to both technical and non-technical audiences, including executive leadership and external partners. p>Employees in this job function are responsible for designing, building, and operating high-throughput backend systems that ingest, process, and serve large volumes of telematics data from connected vehicle fleets. They work at the intersection of distributed systems, data engineering, and API development — delivering reliable, low-latency services that power fleet intelligence products for commercial and enterprise customers. Detroit, Michigan9 days ago i>E-Verify and Right to Work.. Direct implementation of Little Caesar middleware designs and: Maintain SLAs with service providers; Ensure understanding of client requirements regarding middleware services and communicate operations and communicate effectively regarding middleware operations & environment changes.
You will act as a technical leader, shaping the vision and roadmap for our database platform, with a key focus on embedding AI/GenAI capabilities (e.g., Gemini Enterprise, Model Context Protocol, Dataplex, and Knowledge Catalog) into how engineering teams design, build, secure, and operate intelligent data systems at scale. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Auburn Hills, MI30+ days ago This role is ideal for someone who can operate at both the strategic and technical levels: designing decision frameworks, influencing cross-functional partners, and building models that materially improve cost, service, and resilience. Deep experience with predictive modeling (statistical, ML, deep learning), optimization techniques (LP, MIP, constraint programming), and simulation methods (Monte Carlo, discrete event). Auburn Hills, MI30+ days ago Priorities can change in a fast-paced environment like ours, so this role includes but is not limited to the following responsibilities: • Technical Leadership & Strategy • Advanced Analytics & Modeling • Data & Platform Architecture • Experimentation & Product Impact • Knowledge Sharing & Influence. In this new era of mobility, our portfolio of brands is uniquely positioned to offer distinctive and sustainable solutions to meet the evolving needs of customers as they embrace electrification, connectivity, autonomous driving, and shared ownership. li>7+ years of professional experience within data protection and information security, which may include Data Discovery, Data Classification and Rights Management, Data Access Governance, Data Loss Prevention, Cloud Access Security Broker, Encryption, Certificate Lifecycle Management, Cloud Security, SaaS Security. Driving day-to-day engagement execution by communicating updates to clients and Deloitte leadership, supporting delivery teams, and tracking timelines to help achieve on-time and on-budget delivery. |