Top Remote Entry Level Data Engineer Jobs in Dayton, OH

As a Data Engineer I, you will create and maintain scalable code for data needs, improve software processes, develop observability tools for monitoring data jobs, work with Data and MLOps Engineers to integrate data features, mentor teams on software best practices, and innovate solutions to data challenges.

As a Data Engineer at StackAdapt, you will design and implement modular and scalable real-time data pipelines, work on custom ML algorithms, and manage microservices for training and monitoring ML models in a collaborative environment.

The Data Strategist will manage measurement strategies for marketing campaigns, leveraging data analysis, statistical modeling, and customer insights. Key responsibilities include identifying performance insights, maintaining client relationships, presenting findings, and improving reporting processes.

Seeking a skilled Data Operations Engineer to support data annotation production processes by optimizing, maintaining, and scaling data labeling workflows using tools like Labelbox. Responsibilities include scripting in Python, identifying bottlenecks, integrating third-party tools, and providing technical support to project managers and labelers.

As an Entry-Level AI Data Rater, you will engage in data management tasks such as data annotation and rating to help improve AI models. You will follow project guidelines, conduct research, and collaborate with teams to ensure data accuracy. This role offers a flexible schedule with comprehensive learning support for entry-level candidates.

The Data Annotator role involves labeling and curating data to train AI models, including tasks such as identifying objects in images, tagging text, and generating educational content like multiple-choice questions. This position requires attention to detail and expertise in STEM fields, with a focus on ensuring high-quality data for accurate AI model performance.

As a Junior Data Engineer, you will build and support data migration staging environments and warehouses, assist with business and regulatory reporting, profile downstream data for anomalies, collaborate with QA to develop test cases, and create reporting scripts while reviewing peer work.