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Data Scientist Machine Learning Jobs in Ohio (NOW HIRING)

J.P. Morgan

WFP Machine Learning Scientist

Columbus, OH · On-site +1

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data ...

Procter & Gamble

Data Scientist

Cincinnati, OH · On-site

$85K - $122K/yr

Proficient in programming languages such as Python and familiar with data science/machine learning ... libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas. Demonstrated ability to ...

Proctor & Gamble

Data Scientist

Cincinnati, OH

$85K - $122K/yr

Proficient in programming languages such as Python and familiar with data science/machine learning ... libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas.Demonstrated ability to ...

Flexjet

Senior Data Scientist

Cleveland, OH

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... in Data Science, Machine Learning, and AI software engineering, machine learning engineering ...

OCLC, Inc.

Senior Data Scientist

Dublin, OH · On-site

Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and ... As a Senior Data Scientist you will work with stakeholders throughout the organization to identify ...

Flexjet

Senior Data Scientist

Cleveland, OH

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... in Data Science, Machine Learning, and AI software engineering, machine learning engineering ...

Flexjet

Senior Data Scientist

Cleveland, OH · On-site

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... in Data Science, Machine Learning, and AI software engineering, machine learning engineering ...

TQL

Data Scientist

Cincinnati, OH

As a Data Scientist, you'll design, build, and deploy advanced analytics and machine learning solutions that directly support business decision-making. You'll own projects end-to-end--from problem ...

Total Quality Logistics

Data Scientist

Cincinnati, OH · On-site

Total Quality Logistics is seeking a Data Scientist to design, build, and deploy advanced analytics and machine learning solutions that support business decision-making. The role involves owning ...

Flexjet

Senior Data Scientist

Cleveland, OH · On-site

Flexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy ... Responsibilities : • Design and implement enterprise-scale machine learning models, including ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... Lead Data Science Projects * Translate complex business requirements into robust, scalable ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... Lead Data Science Projects * Translate complex business requirements into robust, scalable ...

Sidram Technologies

Data Scientist - w2

Columbus, OH · On-site

Data Scientist Contract to Hire Location - Columbus, OH Summary: Our banking client is seeking a ... Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Ohio

Data Scientist Machine Learning information

See Ohio salary details

$35.7K

$116.7K

$186.8K

How much do data scientist machine learning jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data scientist machine learning in Ohio is $116,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,600.00 and $129,300.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
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Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $116,687 per year, or $56.1 per hour.
WFP Machine Learning Scientist

WFP Machine Learning Scientist

J.P. Morgan

Columbus, OH • On-site, Remote

Full-time

Medical, Retirement

Posted 16 days ago

Job description

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

JOB DESCRIPTION

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase’s call centers, back office, and ~5,200 retail branches.

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data intensive, and of a high level of difficulty, each having significant impact on the business.  You will typically encounter these problems which will be of an unstructured nature, whereby the employee will be expected to quickly assess and comprehend the situation then develop a practical problem solving strategy.  You will be expected to analyze the topic in question, develop solution proposals and review their results and next steps with management for prioritization, timing, and delivery. The AI/ML team is tasked with building next-gen data science solutions that move us closer to real-time inference and decision making.

Job Responsibilities

  • Design and development of Machine Learning, Artificial Intelligence and Statistical models.
  • Participate in the full model development lifecycle, from framing the problem to prepare documentation and passing independent model review (MRGR).
  • Lead AI/ML projects along with mentor and coach junior team members.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Identify and select the correct method to solve the problem while staying up to data on the latest AI/ML research
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Lead and persuade others while positively influencing the outcome of team efforts and help frame a business problem into a technical problem resulting in a feasible solution.

Required Qualifications, Capabilities, and Skills

  • Master’s Degree with 5+ years or Doctorate (PhD) with 3+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • 2+ years of experience leading AI/ML projects with multiple team members
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Deep understanding of math and theory behind AI/ML algorithms.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence. 

Preferred Qualifications, Capabilities, and Skills

  • Advanced expertise with Time Series and Operations Research techniques. 
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders

This position is full time in office Monday - Friday.  This position is not hybrid nor remote.

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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