Deloitte

This role focuses on building and modernizing cyber data and analytics programs, leveraging AI and ML for cyber defense and operations. It involves working with cyber security cloud platforms, data platforms, and AI development tools like vector databases and frameworks. The role requires experience in statistical analysis, machine learning, data mining, and preparing data for analysis using languages like Python and SQL, with a focus on cyber specific use cases.

AI Data Engineer - Manager role focused on leading data architecture and engineering for AI/ML/GenAI solutions. Designs and operationalizes data foundations for LLM-powered applications, including RAG and vector search. Manages delivery teams, partners with stakeholders, and ensures data governance, quality, and monitoring. Blends technical leadership with delivery management and team development, driving engineering standards and outcomes in client environments. Contributes to AI/ML/GenAI technical direction, architectural design, technology selection, and MLOps/LLMOps. Conducts research for scalable AI solutions, leads development of AI models, and collaborates with various teams. Serves as a technical advisor, ensures operational excellence, and addresses risks and ethical considerations in AI implementation.

AI/ML Engineer role focused on developing and maintaining data pipelines, applying machine learning techniques, and building/optimizing AI/ML solutions for client missions, requiring a TS/SCI Polygraph clearance.

Data Operations Engineer for ConvergeHEALTH's Expert Services team, responsible for building and operating cloud-native data pipelines that integrate client healthcare data into Deloitte's Data Studio platform. This role involves data engineering, cloud operations, and applying AI tooling for analytics and anomaly detection, with a focus on creating reliable, decision-ready analytics from complex healthcare data.

Lead Data Expert for Deloitte's AI & Engineering team, focusing on Personnel & Readiness enterprise analytics. This role involves technical leadership in designing and implementing advanced analytics solutions, consultative solutioning, algorithmic innovation (forecasting models), data visualization, and stakeholder engagement. The position requires guiding teams in data wrangling, architecture, automation, and validation, with a focus on federal compliance standards and project lifecycle management. Experience with agentic infrastructure is also mentioned.

Data Foundations Engineer responsible for designing and scaling modern data architectures, building high-performance data pipelines, and enabling analytics and ML use cases. Focuses on data modeling and scalable systems within the Wallet, Payments, and Commerce products, with exposure to MLOps, GenAI/RAG, and LLMs.

Data Foundations Engineer responsible for designing and scaling modern data architectures, building high-performance data pipelines, and enabling analytics and ML use cases. The role requires strong fundamentals in data modeling, scalable systems, and experience with cloud platforms and data processing tools. Exposure to MLOps, GenAI/RAG pipelines, and LLMs is also required, with a focus on the FinTech, Wallet, or Payments domain.

Manager responsible for overseeing end-to-end solution delivery for Kinaxis supply chain planning implementations, involving process design, data analytics, system configuration, and deployment. Requires expertise in optimization methods, statistical analysis, advanced mathematical modeling, and exposure to data science and advanced planning systems.

Develops, implements, and maintains data pipelines and applies advanced data science techniques, including machine learning, spatial analysis, and time-series modeling, to extract insights for mission-critical operations. Builds, tests, and optimizes AI/ML solutions for integration into user-facing tools. Requires TS/SCI Polygraph clearance and 3+ years of experience in data engineering/analytics and 2+ years with Python and SQL.