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Data Science Project Manager Jobs in Columbus, OH

Pwc

Payer Healthcare Data Scientist, Manager

Columbus, OH · On-site

$99K - $232K/yr

Take ownership of projects, ensuring their successful planning, budgeting, execution, and ... The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ...

Impact.com

Technical Project Manager

Columbus, OH · On-site

... and data science teams. Without dedicated operational guidance, complex cross-functional ... The Technical Project Manager (TPM) role is established within the Product Operations sub ...

Impact.com

Technical Project Manager

Columbus, OH · On-site

... and data science teams. Without dedicated operational guidance, complex cross-functional ... The Technical Project Manager (TPM) role is established within the Product Operations sub ...

Impact.com

Technical Project Manager

Columbus, OH · On-site

... and data science teams. Without dedicated operational guidance, complex cross-functional ... The Technical Project Manager (TPM) role is established within the Product Operations sub ...

ApTask Global Workforce

Project Manager

Columbus, OH · On-site

$63.13/hr

Bachelor's Degree in Computer Science, MIS, Engineering or related field, or equivalent work experience * 3+ years of experience in project management and leadership across IT and business functions

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$15

$53

$75

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

As of Aug 13, 2026, the average hourly pay for data science project manager in Columbus, OH is $53.73, according to ZipRecruiter salary data. Most workers in this role earn between $46.49 and $62.88 per hour, depending on experience, location, and employer.

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.

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.
What are popular job titles related to Data Science Project Manager jobs in Columbus, OH? For Data Science Project Manager jobs in Columbus, OH, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Columbus, OH look for? The top searched job categories for Data Science Project Manager jobs in Columbus, OH are:
Data Science Project Manager jobs near you

Data Scientist Vice President - Consumer Bank Marketing Analytics

JPMorgan Chase & Co.

Columbus, OH • On-site

$140 - $190/hr

Other

Posted 8 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description

Are you a data scientist who thrives at the intersection of advanced analytics, business strategy, and measurable impact? At JPMorganChase, we believe the best insights don't just inform decisions — they transform them. Join a team where your work directly shapes how one of the world's largest financial institutions acquires and retains customers, and where your career can grow alongside the impact you create.

As a Data Scientist Lead at JPMorganChase within Consumer & Community Banking Data & Analytics, you will sit at the engine that powers Chase with insights — driving strategy and innovation for Consumer Bank marketing campaigns. You will lead analytics that quantify the effectiveness of marketing investments, optimize multimillion-dollar spend decisions, and influence future campaign strategy through rigorous statistical and business-focused evaluation. This role offers significant learning, collaboration, and mobility opportunities for career development and future growth.

Job responsibilities
  • Lead business- and finance-facing evaluation of customer acquisition quality and portfolio investment optimization, partnering closely with finance stakeholders to translate data into actionable strategy
  • Design and execute geo-based incrementality test reads to support a robust and extensive incrementality testing framework
  • Develop, maintain, and evaluate present value models to support deposit marketing investment decisions and ROI-based portfolio optimization
  • Consult on experimental design and data collection strategies, collaborating with stakeholders and cross-functional data and analytics teams to develop innovative analytical approaches
  • Interpret and present analytical results, findings, and recommendations to senior management and business partners with clarity and precision
  • Provide leadership and mentorship to junior data scientists across the Consumer Bank Marketing Analytics organization, fostering a culture of rigor and continuous learning
  • Participate in innovation projects to advance the team's analytical capabilities and drive adoption of more sophisticated methodologies
  • Maintain a rigorous controls environment to ensure the accuracy, integrity, and timeliness of analytical outputs
  • Collaborate with data professionals across Consumer Bank Marketing Analytics and Test Design teams, championing an inclusive and high-performing team environment
Required qualifications, capabilities, and skills
  • Formal training or certification on data science concepts and 5+ years applied experience
  • Bachelor's and Master's degree in a quantitative discipline such as Data Science, Analytics, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or a related field
  • 5+ years of experience applying statistical methods to real-world business problems
  • 5+ years of hands‑on experience with SQL and at least one analytical programming language, such as Python or R
  • Experience in finance to support budgeting, forecasting, and ROI and cost‑benefit evaluation for business initiatives
  • Hands‑on experience with A/B and incrementality testing methodologies, including experimental design, statistical significance evaluation, and translating test results into business recommendations
  • Demonstrated experience using AI‑assisted development tools such as GitHub Copilot, Claude Code, or similar AI coding assistants to accelerate analysis and code development
  • Experience with data visualization techniques for analysis and executive‑level presentation
  • Superior written and verbal communication skills, with demonstrated ability to present complex findings concisely and effectively to all levels of management and cross‑functional partners
Preferred qualifications, capabilities, and skills
  • Experience in marketing analytics, with a focus on consumer banking, deposits, or financial services
  • Proficiency with Tableau or comparable business intelligence and visualization platforms
  • Demonstrated ability to operate independently on unstructured problems, applying a growth mindset and intellectual curiosity to drive innovation
  • Strong organizational skills with the ability to manage and prioritize multiple workstreams simultaneously
  • Proven ability to build trusted relationships with senior stakeholders and translate business goals into analytical frameworks
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