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Data Science Project Manager Jobs in Ohio (NOW HIRING)

Quadax, Inc.

Data Science Analyst

Cleveland, OH · On-site +1

You'll work closely with product managers, other data scientists, engineers, and business analysts ... Support the creation and maintenance of project documentation * Write user stories, technical ...

Quadax

Data Science Analyst

Middleburg Heights, OH · On-site

You'll work closely with product managers, other data scientists, engineers, and business analysts ... Support the creation and maintenance of project documentation * Write user stories, technical ...

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Data Science Project Manager information

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$15

$54

$76

How much do data science project manager jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for data science project manager in Ohio is $54.67, according to ZipRecruiter salary data. Most workers in this role earn between $47.31 and $63.99 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

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

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in Ohio? For Data Science Project Manager jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Ohio look for? The top searched job categories for Data Science Project Manager jobs in Ohio are:
What cities in Ohio are hiring for Data Science Project Manager jobs? Cities in Ohio with the most Data Science Project Manager job openings:
Data Science Project Manager jobs near you
Data Science Analyst

Data Science Analyst

Quadax, Inc.

Cleveland, OH • On-site, Remote

Full-time

Re-posted 14 days ago

Quadax rating

7.0

Company rating: 7.0 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

164th of 209 rated software companies

Job description

Summary:

Quadax, an award-winning leader in healthcare revenue cycle technology, is seeking a Data Science Analyst to join our Team and help us create the best Revenue Cycle Optimization solution in the industry. You’ll use your knowledge of healthcare revenue cycle business objectives to identify necessary data (SQL, Excel, Snowflake), apply appropriate analytics (BI tools, Azure Foundry) and derive strategic insights to achieve the desired business benefits. You’ll work closely with product managers, other data scientists, engineers, and business analysts to ensure clear definition of all requirements and translating them into value. You’ll leverage data insights to optimize the revenue cycle product design and user experience of our Platform. We use PowerBI for visualization, Snowflake for data management & sharing, and Azure Foundry for all modeling. Local candidates preferred. Open to remote employees ONLY in: OH (if residence is outside a reasonably commutable distance), PA, MI, IN, KY, WV, WI, AL TN, GA, FL, TX, MO, SD, NC.

Responsibilities:

  • Ability to analyze complex data sets and create actionable insights
  • Uses knowledge of business objectives, strategies, and needs to identify opportunities where data can be leveraged to achieve the desired business benefits
  • Understands current data context, processes and availability, and how current data processes and existing data can be leveraged to achieve the desired benefits
  • Prepares and analyzes data. This can include - locating, profiling, cleansing, extracting, mapping, importing, transforming, validating, or modeling
  • Applies query, data exploration and transformation, basic statistical methods, and visualization techniques to create business insights or improve data quality
  • Performs validation and testing to confirm the accuracy of the information created
  • Interprets results of analyses, identifies trends, and issues, and develops recommendations to support business objectives
  • Communicates complex information so that it is easy to understand and influences others to take action based on the useful information provided
  • Facilitate the design and development of product features
  • Interview subject matter experts, customers, and other stakeholders to identify and clarify requirements
  • Establish rapport with stakeholders and ensure that their questions and concerns are clearly documented
  • Present on-time delivery of requirements and user stories/specifications
  • Support the creation and maintenance of project documentation
  • Write user stories, technical requirements for projects including complex business rules, logic flow diagrams, conditional logic, use cases and specific workflows

Qualifications:

  • Healthcare revenue cycle experience with hospitals, providers, and/or other healthcare delivery organizations
  • 2+ years of experience working in Data Science
  • Professional experience with, and more than a basic understanding of AI technology
  • Proficient in building process flow diagrams and data mapping
  • Experience with agile development and software development life cycle (SDLC) processes
  • Proficiency with SQL programming
  • Extensive experience working in a BI environment and familiarity with data warehouses
  • Extensive experience in gathering and documenting business requirements
  • Strong business acumen and data analysis skills and the ability to identify customer needs, analyze them against available solutions, and identify gaps
  • Interprets and presents data analysis results including explanation of statistical and financial techniques used, assumptions made and summary of results
  • Excellent written and verbal communication skills

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