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Ml Data Associate Jobs in Ohio (NOW HIRING)

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as ... With headquarters in Reading, PA, Penske and its associates are driven by a dedication to ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as ... With headquarters in Reading, PA, Penske and its associates are driven by a dedication to ...

Deloitte

Forward Deployed Engineer- AWS

Columbus, OH · On-site

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Deloitte

Senior Forward Deployed Engineer- AWS

Columbus, OH

$100K - $138K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

Deloitte

Forward Deployed Engineer- AWS

Cleveland, OH · On-site

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ... AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI ...

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All JobsMl Data Associate JobsMl Data Associate Jobs in Ohio

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 Aug 9, 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 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 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 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.

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 are popular job titles related to Ml Data Associate jobs in Ohio? For Ml Data Associate jobs in Ohio, the most frequently searched job titles are:
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:
Ml Data Associate jobs near you
Infographic showing various Ml Data Associate job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% 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.

Business Banking Data Owner Senior Associate - Insurance

J.P. Morgan

Columbus, OH

Full-time

Medical, Retirement

Posted 6 days ago

Job description

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

JOB DESCRIPTION

Job Description

As a Data Owner Senior Associate within Business Banking, you will be accountable for data created, provisioned, or consumed across Business Banking products and applications in support of business objectives, advanced analytics, operations, regulatory obligations, and reporting. You will partner with Product, Technology, Analytics, Operations, Risk, Control, and Data Management teams to ensure critical data is clearly defined, properly classified, well-documented, high quality, and protected throughout its lifecycle.

In this role, you will help advance Business Banking's data strategy by defining data requirements, uplifting metadata, supporting data integration into analytics platforms, and executing processes that identify, monitor, and mitigate data risks. You will also help translate business needs into clear data specifications, support remediation of data issues, and maintain documentation that improves data understanding, control, and reuse across the organization.

Job Responsibilities

  • Define and document the scope, meaning, purpose, ownership, and classification of critical Business Banking data.
  • Create plans for the development and delivery of product data to support strategic objectives, operations, analytics, AI/ML use cases, and reporting.
  • Document requirements for data accuracy, completeness, timeliness, lineage, metadata, and consumption across business and technology stakeholders.
  • Execute processes to identify, monitor, and mitigate data risks, including risks related to protection, retention and destruction, storage, use, access, and quality.
  • Partner with Technology, Product, Analytics, Operations, Risk, and Control teams to investigate data issues, identify root causes, and support timely remediation.
  • Support integration of Business Banking data into approved analytics and reporting platforms while maintaining data governance and control expectations.
  • Track workstreams, issues, KPIs, and deliverables to support transparent execution of data initiatives.
  • Maintain comprehensive documentation of data models, data structures, business rules, metadata, and data delivery processes.

Required Qualifications, Capabilities, and Skills

  • Bachelor's degree required.
  • 4+ years of experience in a data-related field, such as data management, data governance, data analytics, data engineering, product data, business analysis, or data quality.
  • Experience working with business or product data, including requirements definition, data documentation, issue analysis, or data controls.
  • Working knowledge of data management, metadata, data quality, privacy/security, retention, and governance concepts.
  • Ability to translate business needs into clear data requirements and partner with technology teams on implementation.
  • Strong analytical, problem-solving, communication, and stakeholder-management skills.
  • Proven ability to manage multiple workstreams and deliver through cross-functional partnerships.
  • Familiarity with SQL, database concepts, cloud or big-data platforms, or data modeling concepts.

Preferred Qualifications, Capabilities, and Skills

  • Business Banking, lending, deposits, servicing, payments, or small business financial services experience.
  • Experience with Snowflake, AWS, Databricks, Hadoop/Spark, Alteryx, Tableau, or similar data platforms/tools.
  • Experience with data governance frameworks, metadata repositories, data catalogs, lineage, data quality rules, or issue management.
  • Familiarity with Agile delivery, JIRA, user stories, technical specifications, or product/data operating models.
  • Experience supporting regulatory reporting, risk management, operational controls, or AI/ML data readiness.

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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