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Nutrition Data Quality Manager Jobs (NOW HIRING)

Figure

Data Quality Manager

San Jose, CA · On-site

$140K - $200K/yr

We are looking for a Data Quality Manager to own data quality at Figure end-to-end - setting the standards, building the tooling, and leading the team that produces the training data behind Helix and ...

Procom Services

Data Quality Analyst

Dallas, TX

Application Development Project Management Quality Assurance Business/Systems Analysis ... Data Quality Analyst Job Details Responsibility : Define, Design, and Build Data quality management ...

Jj

Manager, Data Quality Operations

Titusville, NJ · On-site

The Manager for Data Quality Operations leads and oversees activities to ensure the accuracy, completeness, and consistency of data, acting as a crucial link between business operations and IT ...

Jj

Manager, Data Quality Operations

Raritan, NJ · On-site

The Manager for Data Quality Operations leads and oversees activities to ensure the accuracy, completeness, and consistency of data, acting as a crucial link between business operations and IT ...

Techwave

Data Quality Analyst - Senior Associate Experience: 3 - 5 yrs Location: Hyderabad Summary The Data ... Build and manage requirements traceability matrices, ensuring alignment from business requirements ...

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How much do nutrition data quality manager jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for nutrition data quality manager in the United States is $25.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $30.29 per hour, depending on experience, location, and employer.

What are Nutrition Data Quality Managers?

Nutrition Data Quality Managers are professionals responsible for ensuring the accuracy, consistency, and reliability of nutrition-related data within organizations or research projects. They oversee data collection processes, implement quality control measures, and analyze data to identify and resolve discrepancies. Their work is crucial for supporting evidence-based decisions in nutrition research, policy-making, and program implementation. These managers often collaborate with nutritionists, data analysts, and IT specialists to maintain high standards for data integrity.

What are common challenges faced by a Nutrition Data Quality Manager, and how are they typically addressed?

As a Nutrition Data Quality Manager, one common challenge is ensuring data accuracy and consistency across multiple sources, such as clinical studies, food databases, and electronic health records. Addressing this often involves developing standardized data collection procedures, implementing robust data validation checks, and conducting regular audits. Collaboration with nutritionists, data analysts, and IT specialists is essential to resolve discrepancies and maintain high-quality data. Staying updated on regulatory requirements and best practices in data management also helps mitigate potential quality issues.

What are the key skills and qualifications needed to thrive as a Nutrition Data Quality Manager, and why are they important?

To thrive as a Nutrition Data Quality Manager, you need expertise in nutrition science, data management, and quality assurance, generally supported by a degree in nutrition, dietetics, or data science. Familiarity with data analysis tools (such as Excel, SQL, or statistical software), data quality frameworks, and experience with nutrition databases are typically required. Strong attention to detail, problem-solving abilities, and excellent communication skills are crucial soft skills for this role. These competencies ensure the accuracy, reliability, and usability of nutrition data, which are essential for research, policy development, and public health initiatives.
Infographic showing various Nutrition Data Quality Manager job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 1% Temporary, and 3% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $52,717 per year, or $25.3 per hour.
Data Quality Manager

Data Quality Manager

Figure

San Jose, CA • On-site

$140K - $200K/yr

Other

Posted 14 days ago

Job description

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human-level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.

Data quality is one of the most important and least solved problems in humanoid robotics. The standards, tooling, and methodologies that worked for prior generations of AI, image classification, language, autonomous driving, don't map cleanly onto the multimodal, embodied, sensor-rich data that Helix and our other AI systems learn from.

We are looking for a Data Quality Manager to own data quality at Figure end-to-end - setting the standards, building the tooling, and leading the team that produces the training data behind Helix and our other AI systems. This is not a labeling-team management role. We're looking for a strategic operator and thought partner who will define what the next generation of data quality and annotation looks like for the humanoid robotics industry.

Responsibilities:

  • Own data quality broadly at Figure - setting the strategy, standards, and operating model for how training data is produced, evaluated, and improved across all of our AI systems
  • Own data quality metrics, including accuracy, consistency, rework rates, and guideline adherence across all labeling projects
  • Define the standards, guidelines, QA methodologies, and audit processes for humanoid robot training data, effectively writing the playbook for an annotation discipline that doesn't yet exist outside of a handful of frontier robotics labs
  • Serve as a thought partner to the Helix team across all aspects of AI model development, helping shape what data we collect, how we evaluate it, and how data quality decisions feed into model behavior
  • Develop onboarding and ongoing training programs for new and existing labelers
  • Review edge cases and ambiguous annotations, driving resolution and guideline updates in collaboration with the ML team
  • Partner with engineering to design and develop new internal tooling for annotation, QA, and data review

Requirements:

  • 8-10+ years of experience leading operational or data teams in a fast-paced environment, including hiring, performance management, and coaching
  • Strong analytical and problem-solving skills, with the ability to diagnose quality issues and implement corrective actions
  • Experience managing large-scale data quality or annotation operations
  • Excellent written and verbal communication skills, especially when documenting standards and providing feedback using data
  • Ability to manage competing priorities and time-sensitive deliverables under pressure
  • High attention to detail and a strong quality-first mindset
  • Proficiency in Google Workspace (e.g., Sheets) and operational or workflow management tools

Bonus Qualifications:

  • Experience working with robotics, autonomy, or sensor-derived data
  • 10+ years of experience leading skilled teams operating complex or early-stage technology
  • A passion for helping scale the deployment of learning humanoid robots

The US base salary range for this full-time position is between $140,000 - $200,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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