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Ml Data Associate Jobs in Raleigh, NC (NOW HIRING)

Relay

Associate Product Manager

Raleigh, NC · On-site

As an Associate Product Manager, you will define and deliver products that enhance business ... data sources and durable customer value. • Proactively identify opportunities to leverage AI/ML ...

Relay

Associate Product Manager

Raleigh, NC · On-site

As an Associate Product Manager, you will help define and deliver products that drive business ... data sources and durable customer value. • Proactively identify opportunities to leverage AI/ML ...

First Citizens Bank

Principal AI Architect

Raleigh, NC · On-site

$160K - $240K/yr

... data platforms, or distributed systems. • Deep expertise in AI/ML architecture, including GenAI ... associates. More information can be found at Qualifications: Bachelor's Degree and 10 years of ...

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All JobsMl Data Associate JobsMl Data Associate Jobs in Raleigh, NC

Ml Data Associate information

See Raleigh, NC salary details

$55.9K

$66.1K

$125.4K

How much do ml data associate jobs pay per year?

As of Jul 11, 2026, the average yearly pay for ml data associate in Raleigh, NC is $66,135.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,300.00 and $57,800.00 per year, depending on experience, location, and employer.

What is the salary of ML data operations associate?

The salary of an ML Data Associate typically ranges from $40,000 to $70,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced professionals with specialized skills in data annotation and machine learning tools can earn higher salaries.

What are the key skills and qualifications needed to thrive as an ML Data Associate, and why are they important?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are ML Data Associates?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

Is being an ML data associate stressful?

Working as an ML data associate can be stressful due to tight deadlines, repetitive tasks, and the need for high accuracy in data labeling and management. The role often requires attention to detail, patience, and the ability to handle large volumes of data efficiently.

Is ML a high paying job?

Machine Learning (ML) Data Associate roles typically offer competitive salaries that vary based on experience, location, and industry. Entry-level positions may start lower, but with skills in programming, data analysis, and familiarity with ML tools, salaries can increase significantly with experience and specialization.

How much does an ML Data Associate make?

An ML Data Associate typically earns between $40,000 and $70,000 annually, depending on experience, location, and the complexity of data tasks. Entry-level positions may start lower, while experienced associates with specialized skills in data annotation or labeling can earn higher salaries.

What are some common challenges faced by ML Data Associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.
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Ml Data Associate jobs near you
Associate Product Manager

Associate Product Manager

Relay

Raleigh, NC • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Relay is a rapidly growing tech startup focused on transforming frontline work through innovative technology. As an Associate Product Manager, you will define and deliver products that enhance business operations and user experiences, collaborating closely with engineering and stakeholders to ensure successful product outcomes.
Responsibilities:
• Drive the roadmap for your product area, collaborating with Engineering to deliver viable, high-impact products and ensure timely, high-quality delivery.
• Write detailed user stories for both new features and product enhancements.
• Participate actively in sprint planning and stand-ups, ensuring clarity and momentum throughout the delivery process.
• Develop a deep understanding of your users—whether external customers or internal teams—through interviews, data analysis, and direct engagement.
• Document, analyze, and prioritize feedback through structured discovery work and review of feedback channels.
• Represent the voice of the customer in sprint planning and product reviews to ensure that business and user goals remain aligned.
• Drive product adoption and enablement by developing clear release notes, training materials, and alignment sessions with go-to-market and customer-facing teams.
• Collaborate with our engineering team to fine tune models that harness our proprietary data sources and durable customer value.
• Proactively identify opportunities to leverage AI/ML to enhance our products, derive deeper insights, and unlock new value for users.
• Design and implement strategies that automate manual workflows, allowing customers and internal teams to focus on the work that matters most.
Qualifications:
Required:
• 0–3 years of experience in Product Management, preferably within an enterprise software or SaaS environment.
• A Bachelor's degree in Business, Econ, Computer Science, or related technical or field.
• A strong blend of business and technical acumen, with the ability to engage meaningfully and add value in discussions encompassing both technology and business strategy.
• Curiosity about emerging technologies: A keen interest in staying abreast of cutting-edge technologies, particularly within the AI and automation space, and identifying how they can create new value for users.
• A passion for entrepreneurship with the ability to thrive and react proactively to changing business needs within a dynamic, high-growth startup environment.
• A builder mindset and eagerness to roll up their sleeves and defeat inertia to create customer value.
• Excellent communication and interpersonal skills, with the ability to build strong relationships across internal teams and stakeholders.
Company:
Relay is a cloud based communication platform that offers team communications, operational insights, and workers safety for the leaders. Founded in 2015, the company is headquartered in Raleigh, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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