Director, Product Management – Client Delivery platform – Automotive Planning Solutions

Job Description

• This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Product Management – Client Delivery Platform – Automotive Planning Solutions based in Canada. This is a senior product leadership role responsible for the strategy, roadmap, and evolution of a core client-facing automotive data platform. You will lead a product management team and work closely with engineering, data science, and AI specialists to turn complex data into valuable client experiences. The role combines strategic product ownership with hands-on execution, requiring strong judgment around priorities, tradeoffs, and measurable outcomes. You will shape how AI capabilities are evaluated, productized, explained, and embedded into products that customers rely on for critical decisions. You will also lead customer discovery across areas such as benchmarking, forecasting, trend analysis, compliance, and decision support. Success will require influencing diverse technical and commercial stakeholders while building scalable, reliable, and governed enterprise products. This is an opportunity to shape the future of automotive intelligence in a collaborative, data-rich, and innovation-focused environment.
• Accountabilities Product strategy and roadmap: Own the end-to-end product strategy for the client-facing platform, defining priorities, roadmap plans, success metrics, and value propositions across data products, visualization, usability, and AI-powered capabilities. Product team leadership: Lead, coach, and develop a product management team responsible for data presentation and dashboards, platform usability, AI feature productization, requirements and backlog management, delivery execution, and data structuring. Roadmap and prioritization: Make informed product tradeoffs based on customer value, business objectives, technical considerations, and delivery capacity, ensuring resources remain focused on the highest-impact opportunities. AI product strategy: Establish the strategic direction for AI within the platform, identifying meaningful customer use cases and defining evaluation criteria for AI capabilities before launch, including reliability, explainability, appropriate use, and risk considerations. Technical partnership: Collaborate closely with engineering, data science, and AI teams to translate business needs into technical requirements and ensure data, platform, and AI solutions are scalable, reliable, and effectively integrated. Customer and market discovery: Lead research into how customers use automotive data for benchmarking, trend analysis, forecasting, compliance, and decision support, converting customer insights into actionable product priorities. Data product development: Guide the transformation of complex automotive datasets into intuitive, high-value products, dashboards, and client-facing experiences while maintaining strong data governance and quality. Go-to-market enablement: Partner with sales, marketing, customer success, and research teams on product positioning, documentation, demonstrations, adoption strategies, and customer communications. Stakeholder management: Build strong relationships with senior internal leaders, customers, partners, and cross-functional teams, aligning expectations, resolving tradeoffs, and maintaining momentum across initiatives. Product lifecycle ownership: Oversee the full product lifecycle from discovery and definition through development, launch, adoption, measurement, and continuous improvement within an agile environment. Requirements Bachelor’s degree or equivalent professional experience in Computer Science, Data Science, Engineering, Business, or a related discipline. Demonstrated product leadership experience with data-intensive platforms, analytics products, or similarly complex technology solutions. Strong understanding of data governance, data structures, and data pipeline design, with the ability to work effectively alongside data engineering and technical teams. Proven experience productizing AI/ML capabilities, including defining use cases, evaluating outputs, communicating capabilities and limitations, and integrating AI into customer-facing products. Familiarity with AI connectors and emerging approaches to extending product capabilities through AI. Strong strategic product management skills, including roadmap ownership, prioritization, product discovery, tradeoff management, and success measurement. Demonstrated ability to lead teams and influence outcomes across technical and non-technical functions without relying solely on direct authority. Experience managing the complete product lifecycle, from customer discovery and requirements definition through delivery, launch, adoption, and optimization. Strong communication and presentation skills, with the ability to translate complex technical, data, and AI concepts into clear business and customer outcomes. Experience working in agile product development environments and collaborating closely with engineering, UX, data science, commercial, and customer-facing teams. Strong analytical and decision-making skills, with the ability to balance customer needs, commercial objectives, technical feasibility, scalability, governance, and risk. Nice to have: Experience within the automotive ecosystem, including OEMs, suppliers, mobility, telematics, automotive data, or aftermarket businesses. Nice to have: Familiarity with automotive data domains such as vehicle attributes, manufacturing and parts data, pricing and market signals, production, or demand indicators. Nice to have: Experience delivering enterprise-grade platforms requiring strong reliability, scalability, governance, and data quality. Benefits Competitive compensation: Compensation details are determined based on the role, location, experience, qualifications, and other relevant factors. Leadership opportunity: Lead a dedicated product management team and influence product strategy across a major client-facing data platform. Strategic impact: Shape the development of data-intensive and AI-enabled products used to support important business and automotive decisions. Cross-functional exposure: Work closely with engineering, data science/AI, UX, customer success, commercial, marketing, research, and senior leadership teams. Innovation environment: Opportunity to explore emerging AI approaches and influence how AI capabilities are evaluated and integrated into enterprise products. Career development: Exposure to complex global products, senior stakeholders, enterprise customers, and evolving data and technology practices. Inclusive workplace: Commitment to equal employment opportunity and reasonable accommodations for qualified individuals with disabilities.
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