Human Data Manager, New Grad

Remote | Full-Time | 1 opening

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Overview:

 

Our client is looking for a motivated Human Data Manager, New Grad to join an innovative AI training initiative. This is an excellent opportunity for recent graduates who are passionate about data operations, analytics, process optimization, and project coordination.

 

In this role, you'll apply your analytical and organizational skills to help improve next-generation AI systems by managing high-quality data workflows, optimizing operational processes, and generating actionable insights. No previous AI experience is required—your problem-solving ability, technical aptitude, and willingness to learn are what matter most.

 

Responsibilities:
 

• Design, build, and manage efficient data workflows for annotation, collection, processing, and analysis.
• Establish and monitor key performance indicators (KPIs) to improve operational efficiency.
• Analyze datasets to identify trends and provide actionable business insights.
• Collaborate with cross-functional teams to align data initiatives with business objectives.
• Develop and maintain reporting frameworks that track operational metrics and workflow performance.
• Continuously improve data processes to ensure scalability, quality, and accuracy.
• Maintain high standards of data integrity and validation.
• Take ownership of operational challenges and proactively recommend improvements.

 

Requirements:

 

• Recent Bachelor's or Master's degree in:
• Computer Science
• Data Analytics
• Industrial Engineering
• Operations Management
• Economics
• Finance or a related discipline
• Strong analytical and problem-solving skills.
• Experience with data analysis, annotation, or workflow optimization through academic projects or internships.
• Interest in operational excellence and process improvement.
• Ability to communicate insights clearly, both verbally and in writing.
• Strong organizational skills and attention to detail.
• Ability to thrive in a fast-paced, collaborative environment.
• Eagerness to learn new technologies and methodologies.

 

Preferred Qualifications:

 

• Background in engineering or other technical disciplines.

• Experience with human data projects or operational workflows.

• Familiarity with data visualization tools such as:

• Microsoft Excel

• Tableau

• Power BI
  Basic knowledge of programming languages such as:

• Python

• SQL

• Internship or project experience involving data management, AI/ML, analytics, or process optimization.

 

Benefits:

 

• Fully remote full-time opportunity.
• Work on innovative AI-focused projects.
• Collaborate with experienced professionals across global teams.
• Gain valuable experience in data operations and AI training.
• Career development and continuous learning opportunities.
• Exposure to modern data workflows and operational best practices.
• Supportive and collaborative work environment.
• Opportunity to grow within a fast-paced technology ecosystem.

 

Hiring Process:

 

Step 1: Submit your application and complete the screening questions.

Step 2: Complete a 30-minute AI interview.

Step 3: Hiring manager review.

Step 4: Final selection and onboarding.

Step 5: Begin contributing to project tasks.

 

Regional Hiring Information:

 

This position is being hired across multiple regions to support operational coverage, regulatory compliance, and time-zone alignment. While responsibilities remain consistent worldwide, employment terms may vary depending on your location.

 

Why Join Us?

 

Kick-start your career by working on meaningful projects that combine data operations, analytics, and artificial intelligence. If you're a recent graduate eager to solve real-world problems, learn from experienced professionals, and contribute to the future of AI, this is an excellent opportunity to begin your journey in a fully remote environment.

 

Apply Now:

 

Ready to use your cloud architecture and platform engineering expertise to help shape the future of AI?

 

Apply today and join an exciting remote project solving real-world infrastructure challenges.