Product Manager - Data Driven Products (AI)

Location: Hybrid role based in Stockholm, Sweden

Company

hirify.global is a global SaaS provider of cloud delivery management solutions, processing almost one billion shipments annually across 190 countries through a network of more than 1,000 carriers.

What you will do

• Own the roadmap and product strategy for cross-customer benchmarking, carrier performance prediction, ML-driven carrier recommendations, and related data-driven capabilities.
• Define the data insights layer, including data collection, normalization, information architecture, and exposure to upstream products.
• Partner with an ML Engineer to frame proof-of-concepts, define hypotheses and evaluation criteria, explore results, and make build, kill, or iterate decisions.
• Own quantitative and qualitative intelligence pipelines using shipment telemetry, carrier data, support interactions, delivery exceptions, community feedback, and LLM-extracted insights.
• Validate intelligence use cases with shippers and enterprise customers, define ROI and pricing narratives, and drive integration into existing products.
• Establish anonymization, aggregation, consent, transparency, explainability, and GDPR-compliant data usage standards with Legal and the DPO.

Requirements

• Experience shipping external customer-facing products whose core value was insights, benchmarks, predictions, or recommendations; internal BI, reporting, or dashboards alone is not sufficient.
• Experience driving at least one ML- or AI-powered capability from hypothesis to production, including success criteria, collaboration with data scientists and engineers, and commercial decisions based on model performance.
• 3+ years shipping B2B SaaS products, with experience in business cases, pricing, customer discovery, and enterprise buyer conversations about ROI.
• Technical fluency in ML models, LLM pipelines, data models, pipeline design, normalization, and production data constraints without needing to build models independently.
• Ability to communicate technical and commercial concepts clearly across product, engineering, data science, ML, leadership, customers, and prospects.
• Excellent written and verbal English for strategy documents, ML experiment briefs, customer-facing narratives, and leadership presentations.
• Ability to work with engineers on data models, pipelines, normalization standards, and integration of data-driven capabilities.
• Ability to define legally and ethically sound anonymization, aggregation, consent, transparency, and explainability approaches for multi-tenant B2B SaaS data.

Nice to have

• Experience with time-series or logistics data, including carrier performance modeling, routing optimization, or ETA prediction.
• Familiarity with data lakehouses, feature stores, model registries, and ML observability.
• Hands-on Python data exploration or ML proof-of-concepts using pandas, scikit-learn, or equivalent, or prototyping LLM-based analysis pipelines.
• Experience with GDPR-compliant data products, Nordic or European logistics markets, or building the first data-driven product at a company.
• Previous experience as a data scientist or ML engineer before moving into product management.

Culture & Benefits

• Hybrid work setup in Stockholm.
• Inclusive, diverse, and equal-opportunity workplace.
• Product role within a global SaaS organization operating across multiple European offices and markets.

Hiring process

• Upload a CV in English when applying.