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Product Manager Data Analytics Jobs (NOW HIRING)

Regional Finance

Manager, Data Analytics

Greer, SC · On-site

Act as aknowledge resource, providing training and guidance to others on Ignite capabilities and data usage Required Qualifications * 5+ years of experience indata analytics or data science roles

Gartner

Manager, Data Analytics

Fort Myers, FL · Hybrid

As a Manager, Data Analytics , you will play ahandsonrole supporting and executing strategic and ... it's productive to do so and getting together with colleagues in a vibrant community that is ...

Capital One

Senior Manager, Data Analytics

Mclean, VA · On-site

Coaching and mentoring junior staff As a Senior Data Analytics Manager focused on Product Analytics, you will lead analysts, partner cross-functionally, and set data strategy for a wide range of ...

Sample6 Techcnologies, Inc.

Product Manager

Boston, MA · On-site

Product Manager - Data and Analytics About the company Sample6 Technologies is a spinout of MIT and Boston University, situated at the intersection of synthetic biology, sensor technology and cloud ...

Magna

Manager Data Analytics & Engineering

Lowell, MA · On-site

$105K - $196K/yr

Our products include advanced solutions for urban markets, industrial intralogistics, commercial ... We are seeking a Manager Data Analytics & Engineering to lead the development of scalable data ...

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Product Manager Data Analytics information

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$51.5K

$159.4K

$197K

How much do product manager data analytics jobs pay per year?

As of Jun 20, 2026, the average yearly pay for product manager data analytics in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

For a Product Manager in Data Analytics, age is not a barrier to entering the field. Success depends on skills, experience, and continuous learning, such as mastering tools like SQL, Python, or data visualization software. Many professionals transition into data roles later in their careers and find opportunities based on their expertise and problem-solving abilities.

Is AI replacing data analysts?

Product managers in data analytics oversee the integration of AI tools to enhance data processing and insights, but AI is not replacing data analysts; instead, it automates routine tasks, allowing analysts to focus on complex analysis and strategic decision-making. Skills in data visualization, statistical analysis, and AI tools remain essential for data analysts to add value in organizations.

Do product managers need data analytics?

Product managers need data analytics skills to make informed decisions, prioritize features, and measure product performance. Familiarity with data tools like SQL, Excel, or analytics platforms is often essential for analyzing user behavior and business metrics. These skills help ensure products meet user needs and business goals effectively.

Can a data analyst work as a product manager?

A data analyst can transition to a product manager role if they develop skills in product strategy, project management, and stakeholder communication. While data analysis provides a strong foundation in data-driven decision-making, product managers typically require experience in cross-functional leadership and understanding customer needs. Certifications like Agile or Scrum can also support this career shift.

What are the key skills and qualifications needed to thrive as a Product Manager in Data Analytics, and why are they important?

To thrive as a Product Manager in Data Analytics, you need a strong background in data analysis, product lifecycle management, and business strategy, often supported by a degree in business, computer science, or a related field. Familiarity with data visualization tools (like Tableau or Power BI), SQL, and experience with analytics platforms are typically required, and certifications such as Certified Scrum Product Owner (CSPO) can be advantageous. Exceptional communication, problem-solving, and stakeholder management skills help you bridge technical teams and business objectives. These abilities are crucial for delivering data-driven products that meet user needs and provide measurable business value.

How does a Product Manager in Data Analytics typically collaborate with data scientists and engineers on a project?

As a Product Manager in Data Analytics, you serve as the bridge between business stakeholders and technical teams. You'll work closely with data scientists to define project objectives, ensure that analytical models align with business needs, and prioritize features based on user impact. Collaboration with data engineers is essential for understanding data infrastructure requirements and ensuring reliable data pipelines. Regular communication, sprint planning, and joint problem-solving sessions are core to fostering alignment and delivering successful analytics solutions.

What is the difference between Product Manager Data Analytics vs Data Analyst?

AspectProduct Manager Data AnalyticsData Analyst
Primary FocusOverseeing data-driven product strategies and roadmapsAnalyzing data to generate reports and insights
Skills & CertificationsProduct management, data analytics, SQL, communicationData analysis, SQL, Excel, visualization tools
Work EnvironmentCross-functional teams, product development cyclesData teams, business units, reporting environments
Industry UsageTech, e-commerce, SaaS companiesFinance, marketing, healthcare, tech

Product Manager Data Analytics focuses on guiding product strategies using data insights, while Data Analysts primarily analyze data to produce reports. Both roles require analytical skills and familiarity with data tools, but their responsibilities and scope differ significantly.

What are Product Manager Data Analytics?

A Product Manager Data Analytics is a professional responsible for overseeing the development, strategy, and success of data analytics products or features within an organization. They work at the intersection of business, technology, and data, collaborating with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure analytics solutions meet user and business needs. Their role involves understanding market trends, user requirements, and translating complex data insights into actionable product enhancements. Ultimately, they drive the product lifecycle to deliver value through data-driven decision making.
More about Product Manager Data Analytics jobs
What cities are hiring for Product Manager Data Analytics jobs? Cities with the most Product Manager Data Analytics job openings:
What states have the most Product Manager Data Analytics jobs? States with the most job openings for Product Manager Data Analytics jobs include:
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Product Manager Data Analytics jobs near you
Infographic showing various Product Manager Data Analytics job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 1% Temporary, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Manager, Data & Analytics

Highspring (Formerly MorganFranklin Consulting)

Mclean, VA • On-site

Full-time

Posted 4 days ago

Job description

Job Summary:
Highspring is a consulting firm that focuses on delivering data and analytics solutions to Fortune 100 brands and mid-market firms. The Manager, Data & Analytics will lead projects to design and build data warehouses, develop data pipelines, and implement analytics solutions, while collaborating with clients to address their data challenges and business objectives.
Responsibilities:
• Design and build modern data warehouses and analytics-ready data models.
• Develop scalable, reliable data pipelines using cloud-based data platforms.
• Implement analytics, reporting, and visualization solutions that translate complex data into clear, actionable insights for client stakeholders.
• Partner with client teams to understand business objectives, data challenges, and success metrics through interviews and working sessions.
• Manage discrete project workstreams, balancing technical execution with client communication and delivery timelines.
• Present findings, recommendations, and solution designs to both technical and non-technical audiences.
• Leverage AI-assisted development environments to design, generate, test, and iterate on production-quality analytics and data engineering code.
• Support broader data transformation initiatives, including system implementations, migrations, and modernization efforts.
• Actively participate in internal knowledge sharing, mentoring, and career development activities.
• Support the shaping of the strategic direction of our growing AI/ML, automation, and Data Analytics practice.
• Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping.
• Support data transformation initiatives across a range of service lines, including: M&A Lifecycle (integrations, divestitures, and carveouts), Finance Transformation, Enterprise Data Strategy / Governance Standup, Process Improvement and Automation, System Implementations / Migrations, Data and Automation Strategy and Road mapping (including how companies can leverage AI, ML, and other advanced data modeling concepts).
• Identify insights through use of statistical, algorithmic, mining and visualization techniques.
• Conduct interviews with client stakeholders to identify process and data challenges.
• Document and present findings to both technical and non-technical audiences.
• Develop analytical proof-of-concept prototypes and/ or deliver large-scale analytical platform implementations to fulfill clients’ tactical and strategic requirements.
• Develop business procedures and data management policies for ensuring data accuracy and control.
• Create model documentation, develop implementation roadmaps, and perform knowledge transfers.
Qualifications:
Required:
• 4+ years of data analytics, AI, ML, or GenAI experience
• Tier 1/Tier 2 consulting or professional services firms.
• Experience architecting and developing AI/ML solutions.
• Experience programming in Python, SQL, and/or R.
• Experience using GitHub (e.g., source code management).
• Comprehensive knowledge of modern statistical learning methods.
• Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets.
• Experience with any of the following commercial analytics, automation, and AI/ML tools: Alteryx, Power BI, Tableau, Power Automate, UiPath, Automation Anywhere, AI/ML/GenAI platforms, Informatica, Oracle EDMC, etc.
• Proven ability to lead, motivate and build teams that deliver services and solutions that surpass client expectations.
• Ability to lead workshops, including the gathering/documenting of requirements and use-cases and recommendation of envisioned processes.
• Experience presenting to CXO suite.
• Industry experience within Financial Services, Technology/SaaS, and/or Supply Chain.
• Understanding of typical software development lifecycles (Waterfall and Agile) and their associated lifecycle artifacts.
• Experience with identifying and correcting problems in imperfect data and processes.
• Bachelor's degree in Mathematics, Statistics, Computer Science, Information Systems, or other technology-related field or equivalent number of years of experience
• Flexibility to accommodate travel up to 25%.
Preferred:
• Strong business skills and experience in accounting, corporate finance, and FP&A.
• Familiarity with the M&A transaction lifecycle.
• Master’s degree in Information Technology, Statistics, Physics, Analytics or related field.
• Experience managing technical development by acting as a liaison between the technical team and the user community.
Company:
MorganFranklin Consulting is now Highspring, a leading global professional services organization with three integrated offerings—Consulting, Managed Services, and Talent Solutions. Founded in 1998, the company is headquartered in Mclean, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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