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Data Science Project Manager Jobs (NOW HIRING)

Document analyses, methodologies, and project findings. * Participate in team meetings, knowledge-sharing sessions, and technical discussions. * Learn and apply best practices in data science ...

Sr. Manager AI & Data Science We are seeking a visionary and technically strong Senior Manager of ... Oversee data science project lifecycles, from ideation to production, ensuring alignment with ...

Demonstrated success delivering cross-functional data science projects with measurable impact. * Strong project management skills, including scoping, planning, and risk mitigation. * Ability to ...

Incumbent must have ability to manage a varied workload of projects with multiple priorities and ... in data science will be considere d. The preferred candidate will possess a Master's degree or a ...

This role owns both the work and the team, setting direction across projects, developing talent ... Manage and mentor data scientists and analysts, strengthening both technical expertise and business ...

This role owns both the work and the team, setting direction across projects, developing talent ... Manage and mentor data scientists and analysts, strengthening both technical expertise and business ...

... data science projects - Managing project timelines and deliverables to align with client ... expectations and business objectives What You Must Have - At least a Bachelor's degree - At least 4 ...

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... data science projects - Managing project timelines and deliverables to align with client ... expectations and business objectives What You Must Have - At least a Bachelor's degree - At least 4 ...

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Data Science Project Manager information

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

As of Jul 15, 2026, the average hourly pay for data science project manager in the United States is $57.51, according to ZipRecruiter salary data. Most workers in this role earn between $49.76 and $67.31 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.
More about Data Science Project Manager jobs
What cities are hiring for Data Science Project Manager jobs? Cities with the most Data Science Project Manager job openings:
What states have the most Data Science Project Manager jobs? States with the most job openings for Data Science Project Manager jobs include:
Senior Director Data Science

Senior Director Data Science

Health Care Service Corporation

Chicago, IL • On-site

Full-time

Re-posted 3 days ago


Job description

Job Summary:
Health Care Service Corporation (HCSC) is a purpose-driven company that invests in the professional development of its employees. The Senior Director of Data Science is responsible for planning, managing, and controlling department activities that utilize advanced mathematical and statistical concepts to analyze data and solve business problems, while leading a team of analysts.
Responsibilities:
• Planning, managing and controlling the activities of the department that provides advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems.
• Constructing predictive models, algorithms and probability engines to support data analysis or product functions; verifying model and algorithm effectiveness based on real-world results.
• Leading initiatives to analyze complex business problems and issues using data from internal and external sources; bringing expertise or identifying subject matter experts in support of multi-functional efforts to identify, interpret and produce recommendations and plans based on company and external data analysis.
• Advising business by providing data-based strategic direction to identify and address business issues and opportunities.
• Planning, managing and leading team of analysts that provides advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems.
Qualifications:
Required:
• Bachelor’s degree and 7 years of work experience in a mathematical, statistical, computer science, engineering, physics, economics or related quantitative field; OR 2 or more advanced degrees and 6 years of work experience in a in a mathematical, statistical, computer science, engineering, physics, economics or related quantitative field; OR Ph.D. and 4 years of work experience in a mathematical, statistical, computer science, engineering, physics, economics or related quantitative field; OR 11 years of work experience in an advanced mathematical, statistical , engineering, physics or related quantitative field.
• Leadership and/or management experience.
• 4 years of management experience.
• Learning and growth mindset.
• Customer-focused.
• Interpersonal, verbal and written communication skills.
• Experience in at least five of the following six areas: 1) data analysis and relational-style query languages; 2) machine learning and/or statistical modeling; 3) data visualization; 4) a high-level programming language; 5) distributed computing. 6) understanding of healthcare.
• Microsoft applications including Access, Excel, Word and Power Point.
• A track record of independently delivering or leading the delivery of a complex analytics or data science project.
• Mentoring, managing, or leading junior analytics or data science staff.
• Overseeing the annual budget and allocating resources for various projects and operational needs.
• Translating needs and initiatives into compelling business cases.
• Conducting cost-benefit analyses to justify investments and ensure ROI.
Preferred:
• Masters or Ph.D. in a quantitative field, or Bachelor’s degree with healthcare experience.
• Actuarial Credentials
Company:
Health Care Service Corporation is a customer-owned health insurance company. Founded in 1936, the company is headquartered in Chicago, USA, with a team of 10001+ employees. The company is currently Late Stage.