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Product Manager Data Analytics Jobs in Boston, MA

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 ...

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 ...

... AI-ready analytics. We are looking for a Senior Product Manager, Data Products to own the ... constructs and experiences that data engineers, modelers, data scientists, and emerging AI agents ...

Sr. Product Manager, Data Products

Boston, MA ยท On-site

$137K - $181K/yr

Job Summary : 1872 Consulting is seeking a Senior Product Manager for their Data Product function, who will lead a portfolio of data, analytics, and machine learning products. This role involves ...

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Product Manager Data Analytics information

See Boston, MA salary details

$56K

$173.2K

$214K

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

As of Sep 1, 2026, the average yearly pay for product manager data analytics in Boston, MA is $173,178.00, according to ZipRecruiter salary data. Most workers in this role earn between $153,200.00 and $214,000.00 per year, depending on experience, location, and employer.

What is a 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.

How does a product manager 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 are the key skills and qualifications needed to thrive as a product manager 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.

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.

Do product managers do data analysis?

Product managers often perform data analysis to inform product decisions, track performance metrics, and understand user behavior. They use tools like SQL, Excel, or analytics platforms to interpret data and prioritize features, but they typically collaborate with data analysts or data scientists for complex analysis. Strong analytical skills are valuable in this role to support data-driven decision-making.

What are popular job titles related to Product Manager Data Analytics jobs in Boston, MA?

For Product Manager Data Analytics jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Product Manager Data Analytics jobs in Boston, MA look for?

The top searched job categories for Product Manager Data Analytics jobs in Boston, MA are:

What cities near Boston, MA are hiring for Product Manager Data Analytics jobs?

Cities near Boston, MA with the most Product Manager Data Analytics job openings:

Infographic showing various Product Manager Data Analytics job openings in Boston, MA as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $173,178 per year, or $83.3 per hour.

Staff Product Manager, Data & Analytics

Boston, MA โ€ข Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago


Job description

We are looking for a Staff Product Manager to own Foley's data platform definition and delivery. Data strategy is set at the executive level - this role translates that direction into precise technical requirements, a well-prioritized engineering backlog, and reliable outcomes. You are the bridge between business needs and engineering execution, and you go deep enough on the stack to be a credible peer to the engineers you work with.

The platform model is self-service and distributed. Data access, API access, and intelligence surfaces are democratized - the PM's job is to define and prioritize the capabilities that enable teams to self-serve, not to gate data through a centralized BI function. The backlog is capabilities and paved paths, not reports and data requests.

The ideal background is a former data engineer who moved into product management. Technical depth is a requirement - this person needs to own architecture trade-off decisions, write sharp data requirements, and earn engineering trust through knowledge, not just process.

What you'll doData Platform Definition & Tech Stack Ownership
  • Own Foley's enterprise data model - the data dictionary, entity definitions, and the rules that govern how data is structured and trusted across Dynamics, Salesforce, Ordway, PlanHat, and the data warehouse (including leading the EDM working group)

  • Drive the medallion architecture (Bronze to Silver to Gold) from a product definition perspective - defining quality standards, freshness SLAs, and data contracts in close partnership with engineering

  • Own Silver and Gold layer data definitions - what the data means, and how it can be consumed by applications, agents, and self-service users

  • Prioritize the engineering backlog in partnership with the VP of Engineering - making trade-off calls with full understanding of technical implications

Stakeholder Alignment & Delivery
  • Be the primary data platform partner for business stakeholders across Growth, Sales, Customer Success, Finance, and Operations - enabling self-service access rather than fulfilling individual data requests

  • Own stakeholder communication: proactive status, and crisp escalation of blockers

  • Maintain a weekly touchpoint with the AI Value Creation Office (VCO) - alignment between data platform and AI/data science needs must be exceptionally tight; the AI VCO owns governance and enablement, and this role co-ordinates the technical work that supports it

  • Own delivery against quarterly KRs - track dependencies, surface risks early, and keep work moving across engineering, the analyst, and the AI VCO org

Intelligence Self-Service Platform & API Layer
  • Own the product roadmap for Foley's intelligence self-service platform - the Gold layer as an open consumption surface, the API layer, Chat on Data, dashboards, and paved paths for self-service access

  • Own the API layer as a product - defining what programmatic access looks like, how it is governed, and how applications and downstream services consume the Gold layer

  • Define and maintain the metric layer: conformed metric definitions that serve as the single source of truth for business KPIs across revenue, compliance, and customer health

  • Partner with the data analyst and engineering to enable self-service intelligence - the goal is democratized access, not a centrally managed BI function

  • Drive platform adoption and capability enablement across the organization; identify gaps in paved paths and self-service coverage

Platform Roadmap
  • Own the capabilities and paved paths backlog - the roadmap is platform capabilities, self-service enablement, and infrastructure that unlocks access, not individual reports or data requests

  • Anticipate blockers before they become misses - not after

  • Ramp quickly on Foley's business, customers, user personas, and the regulatory data landscape (FMCSA, DOT compliance, driver qualification) to make context-informed technical decisions

Who you are
  • Strong technical depth in data - you have either built data systems yourself or worked closely enough with data engineering teams to own architecture trade-off decisions with confidence

  • Deep familiarity with data architecture concepts: medallion architecture, data contracts, entity resolution, CDC, API layer design, and pipeline patterns

  • Hands-on familiarity with modern data tooling: dbt, AWS storage solutions (Redshift, S3, Bedrock), graph databases, and pipeline development patterns

  • Ability to write precise technical requirements - engineers should be able to execute against your specs without follow-up clarification

  • Comfort with the self-service / distributed intelligence model - you think in platforms and paved paths, not reports and data requests

  • Strong written and verbal communication - crisp, honest status; no sugarcoating risk; clear writing for both technical and executive audiences

  • Demonstrated ability to ramp quickly in a new domain and earn credibility with engineering through knowledge, not just process

  • Ownership mindset: accountable for outcomes, not just coordination

Nice to Have
  • Former data engineer or analytics engineer who transitioned into product management

  • Experience building or owning a self-service data platform - API layer, democratized access, paved paths for consumers

  • Experience in a compliance, regulatory, or data-as-a-product company where data quality carried real business consequences

  • Familiarity with Amazon Neptune, graph data models, or entity resolution concepts

  • Experience working at the intersection of data and AI - comfortable with the tight dependency between data strategy and ML/data science

  • Experience in a PE-backed, fast-paced environment where priorities shift and resourcefulness matters

About us

At Foley, we’re reimagining how safety-sensitive industries hire, stay compliant, and manage risk. We’ve evolved into a modern SaaS company with an all-in-one, AI-ready platform that helps transportation, construction, distribution, and utility businesses operate faster, smarter, and safer.

As we continue to grow, we’re looking for curious, strategic thinkers who thrive in complexity, are motivated by making an impact, and want to join a team that’s passionate about building great products and supporting customers. Our core values — Teammateship, Grit, and Innovation — guide everything we do. Whether we’re collaborating internally or helping customers, we approach every challenge with optimism, humor, and a shared commitment to success.

Benefits
Foley offers a comprehensive benefits package that includes medical, dental, and vision coverage, a 401(k) with company match, paid time off and holidays, wellness programs, and an employee assistance program.

Equal Employment Opportunity
Foley is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, or any other legally protected characteristic.

Reasonable Accommodations
If you require a reasonable accommodation during the application or interview process, please contact us at careers@foley.io

Employment Status
Employment with Foley is on an at-will basis. Nothing in this job posting or in future communications should be construed as a contract of employment.

Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Privacy Policy: Please see our Applicant Privacy Policy for more information on how Foley processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.

Compensation Range: $160K - $210K