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Ml Data Associate Jobs (NOW HIRING)

iSoftStone

Associate AI Developer

White Plains, NY · On-site

$20/hr

Description iSoftStone, Inc. is seeking an Associate AI Developer to join our Team In New York, NY ... Recently graduated from, a degree/certificate program in Computer Science, AI/ML, Data Science ...

iSoftStone

Associate AI Developer

White Plains, NY

Summary: iSoftStone, Inc. is seeking an Associate AI Developer to help build and ship production ... Recently graduated from, a degree/certificate program in Computer Science, AI/ML, Data Science ...

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Ml Data Associate information

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$57.5K

$68K

$129K

How much do ml data associate jobs pay per year?

As of Jul 6, 2026, the average yearly pay for ml data associate in the United States is $68,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $59,500.00 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
Infographic showing various Ml Data Associate job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 67% Full Time, 30% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $68,039 per year, or $32.7 per hour.
Data Scientist Senior Associate

Data Scientist Senior Associate

JPMorgan Chase & Co

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 16 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 486 frontline employees who took The Breakroom Quiz

54th of 144 rated banks

Job description

As a Data Scientist within the Auto Finance Data & Analytics team, you will leverage advance analytics and AI/ML to support product teams, build analytical solutions, guide strategic business decisions, and enable growth initiatives.

You will partner closely with Product, Technology, Design, Risk, and other cross-functional teams to translate complex business questions into analytical and AI/ML solutions. The ideal candidate is a hands-on analytics practitioner who combines strong technical skills, business judgment, intellectual curiosity, and a passion for applying modern analytics and technology to deliver business outcomes.

Job Responsibilities:

  • Conduct deep-dive analyses to generate actionable insights and recommendations that streamline business processes and uncover potential areas for product innovation and growth
  • Present insights and recommendations to Auto Business leaders using data-driven storytelling to help guide the strategic direction of the organization  
  • Partner with Business, Product and Technology teams to implement data-driven strategies and models/algorithms that drive business growth and customer engagement
  • Develop and apply advanced statistical analyses and mathematical models to analyze complex data trends and patterns
  • Leverage AI tools (e.g., LLM Suite, GitHub Copilot, etc.) to work more efficiently, accelerate analysis, and identify opportunities for innovation
  • Understand end-to-end digital customer engagement funnel and derive insights on how to improve conversion rates
  • Evolve and refine measurement frameworks and KPIs for customer measurement, highlighting anomalies or trends to senior leaders

Required qualification, capabilities and skills:

  • 3+ years relevant experience in AI/ML, data science, or related fields.
  • Strong background in analyzing and translating digital customer behavior data into actionable insights and recommendations for Business leaders. Experience defining KPIs, measurement frameworks, and anomaly monitoring for digital products.
  • Proficient in developing predictive models and utilizing ML algorithms such as logistic regression, KNN, random forest, and Gradient boosting for classification problems.
  • Solid understanding of statistical concepts for data analysis and experience with designing and evaluating A/B experiments.
  • Experience with Adobe Analytics, Tableau, Alteryx, SQL, Python, and AWS.
  • Expertise in prompt engineering and AI-assisted development using LLM Suite, GitHub Copilot Skills, VS Code, etc. to improve LLM output quality and reliability while boosting daily workflow productivity and innovation.
  • Experience in building Conversational AI applications and in orchestrating AI/ML services for building a complete solution.
  • Demonstrated initiative in learning and applying AI/LLM technologies to business problems and projects.
  • Skilled in synthesizing and presenting business insights, recommendations and complex analytical results to executives, business partners, and technical resources across various teams.
     

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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