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Data Annotation Project Manager Jobs in Upper Sandusky, OH

Senior Data Engineer

Findlay, OH · On-site

$99K - $135K/yr

... engineering projects. * Solves complex problems; takes a new perspective on existing solutions ... Data Quality Management - Strong understanding of data quality dimensions, methodologies, and best ...

... Data, Service, Vendors and Business PMO to ensure delivery is well planned, actively managed and ... clearly reported. The role will be responsible for maintaining delivery visibility through Jira ...

Manage capital projects, including scope definition, budgeting, execution, and implementation of ... Analyze production, equipment, and maintenance data to identify trends, perform root cause analysis ...

Manage capital projects, including scope definition, budgeting, execution, and implementation of ... Analyze production, equipment, and maintenance data to identify trends, perform root cause analysis ...

District Manager

Findlay, OH · On-site

$43K - $45K/yr

... and data / photo collection. This role is responsible for recruiting and training assigned ... Maintain 95%+ on-time execution rate for all assigned projects * Foster interactive working ...

Showing results 21-40

Data Annotation Project Manager information

See Upper Sandusky, OH salary details

$16

$55

$78

How much do data annotation project manager jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for data annotation project manager in Upper Sandusky, OH is $55.87, according to ZipRecruiter salary data. Most workers in this role earn between $48.37 and $65.38 per hour, depending on experience, location, and employer.

What is a data annotation project manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.

What are the key skills and qualifications needed to thrive as a data annotation project manager?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

What are some common challenges faced by data annotation project managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What cities near Upper Sandusky, OH are hiring for Data Annotation Project Manager jobs?

Cities near Upper Sandusky, OH with the most Data Annotation Project Manager job openings:

$99K - $135K/yr

Full-time

Re-posted 24 days ago


Marathon Petroleum rating

6.3

Company rating: 6.3 out of 10

Based on 203 frontline employees who took The Breakroom Quiz

68th of 87 rated oil and gas companies


Job description

Job Summary:
Marathon Petroleum Corporation is committed to fostering a collaborative team environment and is seeking a Senior Data Engineer. In this role, you will design, develop, and optimize scalable data pipelines and cloud-based data solutions, while collaborating with various teams to translate requirements into effective data solutions.
Responsibilities:
• Conducts the design, innovation and optimization of data extraction, ingestion and transformation processes.
• Facilitates the development and design of complex data architecture to process and store high-volume data sets.
• Enables the development of complex data pipelines; advocates for and implements data security and privacy measures.
• Conducts complex data quality and processing tasks using open source and cloud services.
• Provide technical expertise during critical incidents.
• Facilitates the adoption of best practices for data security and privacy and collaborates with other departments to ensure seamless data integration.
• Facilitates the implementation of continuous improvements in data processing methods and drives consistency and best practices across data engineering projects.
• Solves complex problems; takes a new perspective on existing solutions; participates in strategic planning sessions for data infrastructure.
• Oversee quality assurance and testing for data solutions.
• Mentors less experienced data engineers.
Qualifications:
Required:
• Bachelor’s Degree in Information Technology, related field or equivalent experience
• 5+ years of relevant data engineering experience
• Strong proficiency in Python, SQL, Spark, and orchestration tools such as Azure Data Factory and/or Databricks Workflows
• Familiarity with big data technologies and frameworks, such as Hadoop, Spark, and distributed computing, for processing and analyzing large volumes of data
• Knowledge of cloud-based data platforms, such as AWS, Azure, or GCP, and their associated services for data storage, processing, and analytics
• Ability to establish and oversee a set of procedures, policies, and standards that ensure the effective and efficient management of an organization's data assets
• Proficiency in integrating data from various sources, including structured and unstructured data, using technologies such as ETL (Extract, Transform, Load) processes, data pipelines, and data ingestion frameworks
• Skill in designing and implementing data models that align with business requirements, ensuring data integrity, performance, and scalability
• Data operations refer to the various actions and processes involved in managing, manipulating, and analyzing data throughout its lifecycle
• Data pipelines are a set of processes that enable the flow of data from one or multiple sources to a destination
• Ability to understand and implement practices that ensure the protection and confidential handling of personal and sensitive information
• Strong understanding of data quality dimensions, methodologies, and best practices to establish and maintain data quality standards and processes
• Knowledge of data privacy regulations, cybersecurity best practices, and techniques for protecting sensitive information and ensuring compliance
• Knowledge of monitoring and observability tools and practices for tracking data pipeline performance, data quality, and system health
• A set of practices that combines software development and information-technology operations which aims to shorten the systems development life cycle and provide continuous delivery with high software quality and a security first approach
• Applies a computer language to communicate with computers using a set of instructions and to automate the execution of tasks
• Proficiency in metadata management solutions to enable efficient data discovery, data lineage tracing, and data asset management
• NoSQL databases are a type of database management system that provides a flexible and scalable approach to storing and retrieving data
• Real-time processing refers to the method of handling data or performing computations immediately as they occur, without any noticeable delay
Company:
Marathon Petroleum Corporation (MPC) is a leading, integrated, downstream and midstream energy company headquartered in Findlay, Ohio. Founded in 2005, the company is headquartered in Findlay, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About Marathon Petroleum

Sourced by ZipRecruiter

Marathon Petroleum Corporation, headquartered in Findlay, Ohio, US, is a leading independent petroleum refining, marketing, and transportation company. Their official website can be found at marathonpetroleum.com. The company, part of the energy sector, was established in 1887, making it one of the oldest petroleum companies in the US. It operates an integrated refining, marketing and transportation system concentrated primarily in the Midwest, Northeast, East Coast, Southeast and Gulf Coast of the United States. This includes refineries, pipelines, and terminals that process and transport crude oil and refined products.

Industry

Oil and gas extraction

Company size

10,000+ Employees

Headquarters location

Findlay, OH, US

Year founded

1887