5+ years of product management experience, with 3+ years focused on data platforms or AI/ML products.
Proven ability to leverage proprietary data as a strategic asset, enhancing model performance or creating benchmarks.
Strong understanding of data architecture, including modeling, pipelines, and master data management.
Experience collaborating with ML teams on training data and feedback loops for machine learning systems.
Proficient in structuring and normalizing complex, multi-source enterprise data, particularly from ERP or procurement systems.
Knowledge of data rights and governance in B2B SaaS environments, including anonymization practices.
Technical fluency in SQL and data quality assessment.
Responsibilities
Own the strategy and roadmap for capturing and structuring customer and sourcing data.
Identify and prioritize data that provides a competitive advantage, such as pricing and negotiation outcomes.
Design strategies to capture valuable signals throughout the sourcing process, ensuring data integrity.
Define data models and taxonomies for unifying data across various platforms and systems.
Create feedback loops that enhance agent performance through improved sourcing outcomes.
Collaborate with AI and engineering teams to ensure data usability for models and agents.
Establish data-powered product capabilities that deliver unique customer value based on aggregated data.
Work with legal and security teams to set frameworks for data rights and consent management.
Set standards for data quality and measure the value of the data asset through relevant metrics.
Manage the roadmap for customer-facing analytics and reporting tools.
Benefits
Opportunity to shape a proprietary data asset that enhances market position.
Collaborative environment with cross-functional teams including AI and engineering.
Focus on innovative data strategies that drive customer insights and outcomes.
Engagement in high-impact projects that influence product development and customer success.
Commitment to data governance and compliance with industry standards.
Full Job Description
The Role
Every sourcing event run on Glo generates structured data on purchase intent, supplier pricing and performance, negotiation outcomes, and award decisions. As a Data Product Manager at Globality, you will own the strategy for capturing, structuring, and compounding that data into a proprietary asset that makes Glo smarter with every event and makes Globality's market position defensible. You will set the requirements forwhat data we collect, how it is structured and governed, and how it flows back into the platform to improve agent performance and customer outcomes. You will also own the analytics and benchmark products that give customers insight into their sourcing results. You will partner with Engineering, Machine Learning, the AI Product Manager, and Product leadership to run data as a product with its own roadmap, users, and measurable return.
What You Will Do
Own the data product strategy and roadmap, defining how Globality captures, structures, and compounds customer and sourcing data into a defensible, proprietary asset.
Identify which data creates durable competitive advantage, including purchase intent, should-cost benchmarks, supplier pricing and performance, negotiation outcomes, and award decisions, and prioritize investment accordingly.
Design the instrumentation strategy that captures high-value signals at every step of the intake-to-award process,in partnership with the product managers who own each workflow, closing gaps where data is lost or left unstructured.
Define canonical data models, taxonomies, and entity resolution for suppliers, categories, and commercial terms so data from every customer, ERP platform, and procurement system can be unified and reused across the platform.
Build the feedback loops that turn sourcing outcomes into training data, evaluation sets, and benchmarks that improve Glo's agents, including target pricing, supplier discovery, negotiation strategy, and award recommendations.
Partner with the AI Product Manager, Machine Learning and Engineering to make data readily usable by models and agents, including labeled datasets, feature pipelines, and retrieval sources.
Define data-powered product capabilities, such as market pricing and should-cost benchmarks, that deliver customer value only Globality's aggregated data can provide, working with Product leadership to decide which are worth building.
Work with Legal, Security, and Sales to establish the data rights, consent, and contractual frameworks that allow Globality to use aggregated and anonymized data across customers.
Set standards for data quality, coverage, and freshness, and measure the value of the data asset through metrics such as category coverage, model performance lift, and improvement in customer outcomes.
Own the roadmap for customer-facing analytics, such as spend and savings reporting and customer insight dashboards, in partnership with Product leadership.
Define the metrics that show customer results, including cycle time, savings, spend under management, supplier participation, and award outcomes, keep their definitions consistent across products, and document them in a shared data dictionary.
Ensure customer data is handled in line with SOC 2 Type 2, ISO 27001:2022, GDPR, and CCPA requirements, including data segregation and access controls.
What You Bring
5+ years of product management experience, including 3+ years owning data platform, data infrastructure, or AI/ML data products
A track record of turning proprietary data into a strategic asset, such as data network effects, industry benchmarks, or training data that measurably improved model performance
Deep understanding of data architecture, including data modeling, pipelines, warehouses and lakehouses, entity resolution, and master data management
Experience working closely with ML teams on training data, labeling, evaluation datasets, and feedback loops for machine learning or LLM-based systems
Experience structuring and normalizing messy, multi-source enterprise data, ideally from ERP, procurement, or financial systems
Working knowledge of data rights, privacy, and governance in multi-tenant B2B SaaS, including anonymization and aggregation of customer data
Strong technical fluency, including SQL, with the ability to assess data quality and validate assumptions independently
A strategic, business-oriented mindset, with the ability to articulate the economic value of data and make the case for investment to executive leadership
Experience turning customer or operational data into analytics, dashboards, or benchmarks used by external customers
Experience with procurement, sourcing, or spend data is a strong plus
The anticipated annual base salary range for this position is $150,000 - $250,000. Actual compensation may vary based on factors such as experience, skills, and location. This information is provided in accordance with the California Equal Pay Act.
