Product Manager, AI & Data Analytics

Darum lohnt es sich

Responsibilities • Define and drive product strategy, roadmap, and priorities for AI, analytics, data fusion, and intelligence-related product capabilities. • Translate complex customer, operational, and business needs into clear product requirements and priorities. • Work closely with engineering to shape feasible, valuable, and scalable product solutions. • Partner with sales, pre-sales, customer-facing teams, and leadership to understand customer needs, market opportunities, and commercial priorities. • Balance long-term product vision with short-term delivery needs in a fast-changing environment. • Identify opportunities for innovation, product differentiation, automation, and better use of AI/data capabilities. • Use customer feedback, user behavior, product data, and market insights to improve product value, usability, and adoption. • Conduct competitive analysis and evaluate external products, APIs, integrations, and technologies that could enhance our product offering. • Manage stakeholder expectations, align conflicting priorities, and drive clear product decisions. • Support product adoption across different markets, customers, and use cases.

Requirements • 3+ years of experience in product management, ideally in complex B2B technology environments. • Proven experience managing complex products with multiple stakeholders, technical dependencies, and business priorities. • Experience with AI, analytics, machine learning, data platforms, intelligence products, fraud/risk solutions, or other data-heavy products. • Strong understanding of B2B product dynamics, including customer discovery, sales cycles, pilots, renewals, adoption, and commercial impact. • Ability to connect product decisions to customer value, revenue opportunities, and business outcomes. • Strong stakeholder management skills, with experience aligning engineering, sales, customers, and senior leadership. • Experience working in a startup, scale-up, or fast-changing product environment. • Ability to work independently, take ownership, and drive product direction without heavy guidance. • Strong technical understanding of cloud-based platforms, APIs, data flows, and data-driven products. • Excellent communication skills, with the ability to clearly explain product decisions, trade-offs, and priorities. • Agile mindset, flexibility, and comfort with ambiguity, changing priorities, and short delivery cycles. • Nice to have: Experience in public safety, intelligence, law enforcement, fraud detection, risk, compliance, or cybersecurity products. • Experience with graph analysis, data visualization, maps, dashboards, or big data platforms. • Experience with user behavior analysis tools such as LogRocket or similar. • Experience working with AI-powered features, decision-support tools, or automation products. • Experience supporting sales or pre-sales activities through product demos, discovery, or customer-facing product discussions.