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Ml Data Associate Jobs in Texas (NOW HIRING)

J.P. Morgan

Data Scientist Senior Associate

Plano, TX · On-site

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 ...

1 point system

Solution Architect

Plano, TX · On-site

$60.25 - $79.50/hr

AI-102 (Azure AI Engineer Associate), DP-100 (Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications. Azure Solutions Architect

KPMG US

Senior Associate, AI Engineer

Dallas, TX · On-site

$54.75 - $70.50/hr

They are seeking a Senior Associate, AI Engineer to develop and test AI models, assist with data preparation for AI/ML model training, and integrate AI solutions into enterprise applications.

KPMG US

Senior Associate, AI Engineer

Houston, TX · On-site

$52.75 - $68/hr

They are seeking a Senior Associate, AI Engineer to develop and test AI models, assist with data preparation for AI/ML model training, and integrate AI solutions into enterprise applications.

Stackruit Ltd.

Generative AI Engineer

Dallas, TX · On-site

$100 - $130/hr

AI-102 (Azure AI Engineer Associate) or DP-100 (Azure Data Scientist Associate) or Databricks ML Data Scientist. * Familiarity with GitHub or Azure DevOps. * Prior consulting and business development ...

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Ml Data Associate information

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$53.6K

$63.4K

$120.2K

How much do ml data associate jobs pay per year?

As of Aug 23, 2026, the average yearly pay for ml data associate in Texas is $63,389.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $55,400.00 per year, depending on experience, location, and employer.

What is an ml data associate?

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 are the key skills and qualifications needed to thrive as an ml data associate?

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 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.

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.

How do I become an ML Data Associate?

To become an ML Data Associate, candidates typically need a high school diploma or equivalent, along with strong attention to detail and organizational skills. Familiarity with data management tools, basic understanding of machine learning concepts, and experience with data annotation or labeling are often required. Some roles may also require knowledge of programming languages like Python or experience with data annotation platforms.

What skills do you need for a machine learning data associate job?

A machine learning data associate needs strong analytical skills, attention to detail, and proficiency in data management tools like Excel, SQL, or Python. Knowledge of data cleaning, labeling, and basic understanding of machine learning concepts are also important for the role.

What are popular job titles related to Ml Data Associate jobs in Texas?

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What job categories do people searching Ml Data Associate jobs in Texas look for?

The top searched job categories for Ml Data Associate jobs in Texas are:

What cities in Texas are hiring for Ml Data Associate jobs?

Cities in Texas with the most Ml Data Associate job openings:

Ml Data Associate jobs near you
Infographic showing various Ml Data Associate job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $63,389 per year, or $30.5 per hour.

Data Scientist Senior Associate

J.P. Morgan

Plano, TX • On-site

Full-time

Medical, Retirement

Re-posted 17 days ago

Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

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.
     

ABOUT US

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

ABOUT THE TEAM

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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