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Data Science Associate Jobs in Ohio (NOW HIRING)

Benchmark Gensuite

[US] Data Analytics Associate

Mason, OH · On-site

$55K - $56K/yr

Data Analytics Associate Full Time Hybrid - Mason, OH Innovate with Benchmark Gensuite as a Data ... Must be able to clearly understand and articulate a data science problem and work on it ...

Benchmark Gensuite

[US] Data Analytics Associate

Mason, OH · Hybrid

$55K - $56K/yr

Data Analytics Associate Full Time Hybrid - Mason, OH Innovate with Benchmark Gensuite as a Data ... Must be able to clearly understand and articulate a data science problem and work on it ...

Benchmark Gensuite

[US] Data Analytics Associate

Mason, OH · On-site

$55K - $56K/yr

Data Analytics Associate Full Time Hybrid - Mason, OH Innovate with Benchmark Gensuite as a Data ... Must be able to clearly understand and articulate a data science problem and work on it ...

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All JobsData Science Associate JobsData Science Associate Jobs in Ohio

Data Science Associate information

See Ohio salary details

$54.7K

$64.7K

$122.6K

How much do data science associate jobs pay per year?

As of Jul 21, 2026, the average yearly pay for data science 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.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

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

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Ohio? The most popular types of Data Science jobs in Ohio are:
What are popular job titles related to Data Science Associate jobs in Ohio? For Data Science Associate jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Ohio look for? The top searched job categories for Data Science Associate jobs in Ohio are:
What cities in Ohio are hiring for Data Science Associate jobs? Cities in Ohio with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 68% Full Time, 29% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $64,684 per year, or $31.1 per hour.
Data Science Senior Associate - Digiops Analytics

Data Science Senior Associate - Digiops Analytics

J.P. Morgan

Columbus, OH • On-site

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.

Job description

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

JOB DESCRIPTION

Come join a team that improves Chase's self-service experiences for millions of customers.

As a Data Science Senior Associate at JPMorganChase on the DigiOps Analytics team, you will support an extensive portfolio by using behavioral and customer journey data to provide recommendations that enhance the customer experience and build long-term, profitable customer relationships. You will help define objectives and key results, develop and measure A/B tests, answer strategic analytical questions, and create analytical plans to drive outcomes. You will deliver clear, actionable insights while partnering closely with Product, Technology, Design, and Analytics teams, and you will share learnings broadly across stakeholders.

Job responsibilities

  • Analyze, visualize, and tell compelling stories through data about customer behaviors and digital journeys
  • Increase data-informed decisions through establishing partnerships, best practices, and clear communications
  • Create experiment and analytical plans to measure the customer impact of new strategies and operational improvements
  • Identify opportunities to drive business outcomes through insights, objectives and key results development, and deep-dive analysis
  • Collaborate with cross-functional teams to identify and prioritize initiatives that drive operational efficiencies and improve customer experience
  • Promote and share successes and learnings across key stakeholders and partner teams to drive increased awareness and adoption of a journey-led approach to innovation
  • Partner with the Modeling Center of Excellence and other analytics teams to support predictive modeling, machine learning, and advanced analytics projects
  • Ensure data is highly governed and controlled, coordinating with Data Owner Leads as needed
  • Provide consultation for the broader Data & Analytics organization as an expert in behavioral and customer journey data

Required qualifications, capabilities and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • 3+ years of experience analyzing customer experiences, digital products/usage, or in digital operations, strategy, or a related field
  • Detail-oriented and structured thinker with a passion for analyzing data and providing clear actionable insights
  • Ability to organize complex business problems and translate them into analytical plans, and execute with high quality
  • Strong communication and presentation skills to deliver insights to executives and partner with other teams
  • Proficiency with SQL
  • Experience with web analytics
  • Bachelor's degree required

Preferred qualifications, capabilities and skills

  • Experience with analytical tools such as Copilot, Python, R, Alteryx, Tableau, and Adobe Analytics
  • Experience working with big data environments (for example, Hadoop, Teradata, Snowflake)
  • Experience with A/B testing
  • Experience in financial services or a similar industry
  • Strong slide-writing and presentation skills to deliver analytical insights

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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