Human Data Manager, New Grad

Remotebridge; United States; Remote; USD 60,000 - 90,000; Full time

Job summary

Remotebridge is seeking a Human Data Manager, New Grad, to join our remote-first team in the United States. You will help train next-generation AI systems by shaping data inputs, annotations, and analyses.

No prior AI experience is required; your domain knowledge and data skills drive model learning and performance. You will design robust data workflows, monitor KPIs, and deliver insights that improve efficiency and data quality, collaborating closely with product, engineering, and operations

Qualifications

• Recent graduate (Bachelor's or Master's) in CS, Data Analytics, Industrial Engineering, Operations Management, Economics, Finance or related field.
• Technical aptitude with data analysis, annotation, or workflow optimization experience.
• Familiarity with operational processes and a passion for efficiency.
• Ability to clearly present data-driven insights in writing and speaking.

Responsibilities

• Design, build, and manage data workflows for annotation, collection, processing, and analysis.
• Establish and monitor KPIs to optimize performance and decision-making.
• Analyze datasets to uncover actionable insights and present recommendations.
• Collaborate cross-functionally to align data strategies with business goals.
• Develop reporting frameworks tracking key metrics and workflow improvements.
• Refine processes to ensure scalability, data integrity, and quality.

Skills

Data analysis

Data annotation

Workflow optimization

Communication of insights

Collaboration

Python/SQL

Education

Bachelor's or Master's in CS/Analytics/Engineering

Tools

Python/SQL

Tableau/Power BI

Excel

Job description

Job Title: Human Data Manager, New Grad

Job Type: Full-time

Location: Remote

Job Summary:

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities

• Design, build, and manage robust data workflows for accurate annotation, collection, processing, and analysis.
• Establish and monitor KPIs to optimize operational performance and drive data-driven decision-making.
• Analyze datasets to uncover actionable insights and present recommendations that accelerate efficiency.
• Collaborate cross-functionally to align data strategies with overarching business objectives.
• Develop and maintain comprehensive reporting frameworks tracking key metrics and workflow improvements.
• Continuously refine processes to ensure scalability, maintain data integrity, and uphold quality standards.
• Demonstrate ownership and a proactive, hands-on approach to identifying and solving operational challenges.

Required Skills and Qualifications

• Recent Bachelor's or Master's graduate in Computer Science, Data Analytics, Industrial Engineering, Operations Management, Economics, Finance or other related fields.
• Technical aptitude with demonstrated experience in data analysis, annotation, or workflow optimization.
• Familiarity with operational processes and a passion for increasing efficiency.
• Ability to interpret and communicate data-driven insights clearly and persuasively, both in writing and verbally.
• Strong drive to learn, thrive under pressure, and a willingness to work hard in a fast-paced environment.
• Excellent collaboration skills and attention to detail in managing data quality and validation.

Preferred Qualifications

• Background in engineering or technical fields with operational focus or human data projects.
• Experience with data visualization tools (such as Excel, Tableau, Power BI) or programming languages (such as Python, SQL).
• Internship or project-based experience in data management, AI/ML, or process optimization.

Regional Hiring Notes

This role is being hired in parallel across multiple regions due to coverage needs, compliance requirements, and time-zone alignment. Responsibilities and expectations are identical; employment terms vary by region.