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Ml Data Associate Jobs in Ohio (NOW HIRING)

Data Strategy-Manager

Cincinnati, OH · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

Data Strategy-Manager

Cleveland, OH · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in ...

Data Strategy-Manager

Columbus, OH · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in ...

Data Governance- Manager

Cincinnati, OH · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

Data Governance- Manager

Columbus, OH · On-site

$99K - $232K/yr

... Associate - SAP Master Data Governance (MDG) - SnowPro Core / SnowPro Advanced - Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary ...

Showing results 41-60

Ml Data Associate information

See Ohio salary details

$54.7K

$64.7K

$122.6K

How much do ml data associate jobs pay per year?

As of Sep 2, 2026, the average yearly pay for ml data associate in Ohio is $64,684.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,100.00 and $56,600.00 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 job categories do people searching Ml Data Associate jobs in Ohio look for?

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

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

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

Infographic showing various Ml Data Associate job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $64,684 per year, or $31.1 per hour.

Applied AI ML Senior Associate

JP Morgan Chase

Columbus, OH • On-site

Full-time

Medical, Retirement

Re-posted 25 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 499 frontline employees who took The Breakroom Quiz

72nd of 174 rated banks


Job description

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. In this role, you'll apply strong technical judgment to choose the right approaches (including modern LLM-based methods where appropriate), evaluate performance with rigorous metrics, and ensure solutions are reliable, secure, and scalable in real-world environments. You'll also contribute to improving data quality and feedback loops, monitoring models in production, and continuously iterating to reduce agent effort, shorten resolution times, and increase consistency and quality across operational workflows.

As an Applied AI Engineer Senior Associate within the Consumer & Community Banking Machine Learning team, you will work with agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities

  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software  Development Life Cycle
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
  • Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
  • Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
  • Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
  • Promote software and model quality, integrity, and security across the organization

Required qualifications, capabilities, and skills

  • BS in Computer science or similar fields with 5+ years experience or MS in Computer science or similar fields with 2+ years experience, with training and work experience in LLM/NLP and search.  
  • Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
  • Experience in  machine learning frameworks, ML Ops tools and practices. 
  • Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
  • Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API) and RAG based solutions (e.g., open search) 
  • Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD) 

Preferred qualifications, capabilities, and skills

  • Optional, great to have - experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems). 

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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