Director Analytics Product and Solutions

As Director - Analytics Products and Solutions, you will lead MiQ's Local Products capability, turning high-value commercial and client problems into scalable analytics and data products that can be reused across markets. You will bring deep analytics and data science leadership, strong product thinking, and sufficient engineering fluency to take solutions from 0-> 1 and 1-> N.

Responsibilities:

• Working closely with Commercial, Product, Data Science and Engineering, you will determine which problems Local Products should solve, how analytical capabilities should be productised, and when solutions should scale into MiQ's central platforms.
• Ensure we build the right capabilities, not simply more capabilities - balancing commercial value, analytical differentiation, scalability, adoption, and speed.
• Lead a multidisciplinary organisation through empowered leaders, setting portfolio direction, challenging key product and technical decisions, and creating reusable standards while keeping day-to-day solutioning and delivery ownership with your leads.
• Director LP owns: LP capability strategy, analytics-product strategy, portfolio prioritisation, productisation and lifecycle/value.
• Commercial Product owns: market/client opportunity, commercial requirements, GTM and commercial adoption.
• Engineering/P and T owns: production engineering architecture, infrastructure, security, reliability and platform scale.
• Work at the intersection of: Data Science organisation - partnering with the DS leadership to translate models and analytical capabilities into production-ready product features.
• Local Product and Commercial teams - shaping products that drive measurable business outcomes for key markets.
• Engineering and Platform teams - ensuring products are robust, scalable, well-tested, and cost-efficient.
• Data and Analytics (DnA) - leveraging reusable data assets and analytical capabilities.
• Product Vision, Strategy, Identity, and Roadmap.
• Ownership: Define the role of Local Products within MiQ's ecosystem.
• As the agency solutions layer (planning, activation, signal generation).
• Distinct from Sigma (scale layer) and Measurement and Insights.
• Clearly articulate: What LP builds, what LP does NOT build.
• How LP supports markets vs Product vs DnA. Partner with central Product teams to transition scalable capabilities into Sigma.
• Avoid parallel/duplicate builds.
• Evolve LP from a feature factory to a capability-driven organisation
• Translate ambiguous business problems from markets into clear product hypotheses, technical problem statements, and prioritised roadmaps to solve them.
• Prioritise across multiple products and initiatives using impact, effort, and strategic alignment frameworks (Ex: RICE, MoSCoW, Cost of Delay); ensure product and solution OKRs are met across the portfolio.
• Own the product lifecycle end-to-end - from ideation and proof-of-concept through build, launch, adoption tracking, iteration, maintenance, and sunset decisions.
• Make deliberate build vs buy vs partner decisions - evaluating technology options, open-source components, and third-party integrations against in-house development for each product capability.
• Partner with Product Management and commercial stakeholders to validate opportunities and translate market needs into technically sound, deliverable product plans.
• Provide hands-on technical leadership across solutioning and product architecture - designing systems that are robust, extensible, and built to scale across markets, in line with scalability best practices.
• Bring sufficient engineering fluency to challenge architecture, deployment, reliability, and scalability decisions, working with Engineering to establish appropriate production standards.
• Set and challenge product quality, reliability, and production-readiness standards in partnership with Engineering.
• Drive adoption tracking and instrumentation - ensuring every product has clear usage, engagement, and adoption metrics built in from day one.
• Bring strong Scrum ceremonies expertise and best practices - leading and coaching teams through sprint planning, stand-ups, backlog grooming, sprint reviews, and retrospectives to drive predictable, high-quality delivery.
• Maintain strong awareness of and evaluate the latest data and analytics tooling - including Databricks, Spark, Gathr, and other emerging platforms - to inform build decisions and keep the technology stack current.
• Prioritisation and Product Governance.
• Establish a centralised intake and prioritisation model across markets.
• Ensure all work is evaluated against: commercial impact, Scalability, Reusability, Sigma alignment.
• Act as the single-threaded owner of roadmap decisions and deployment excellence, making trade-offs across: market demand, engineering capacity, strategic priorities.
• Reduce: ad-hoc builds, duplication, low-impact features.
• Provide technical leadership across the full SDLC)requirements analysis, system design, implementation, testing, deployment, monitoring, and ongoing maintenance.
• Establish and own the QA/QC framework for the portfolio: automated testing strategies (unit, integration, regression, performance), test coverage standards, and quality gates that products must clear before release.
• Own the maintenance and upgrade strategy for shipped products - including SLA definitions, incident management, technical debt tracking, and upgrade pathways that keep products healthy and supportable over time.
• Champion the integration of AI accelerators into the product development workflow - evaluating and embedding tools such as AI-powered code assistants (Ex: Copilot, Cursor), automated code review, AI-driven test generation, intelligent documentation, and GenAI-powered prototyping to boost developer productivity and reduce cycle time.
• Partner with the Data Science organisation to productionise models and analytical capabilities - defining clear contracts, integration patterns, performance benchmarks, and monitoring for ML components within products.
• Drive design thinking and user-centric development practices - ensuring local products are built with deep empathy for end-user workflows, not just technical elegance.
• People Leadership, Coaching and Culture: Lead and grow a high-performing product + technical team.
• Build leaders who can: think commercially, prioritise effectively, operate cross-functionally.
• Shift team mindset from delivering requests to solving problems at scale.
• Build a high-trust culture that emphasises ownership, quality craftsmanship, delivery excellence, learning, and autonomy.
• Coach technical leaders on stakeholder management, storytelling, product thinking, and commercial awareness so they can independently drive workstreams and influence senior partners.
• Foster cross-functional fluency - developing team members who are equally comfortable discussing system architecture, product metrics, and business impact.
• Upskill teams on modern development practices and AI-powered tooling - ensuring the organisation stays current with evolving best practices.
• Define and support learning and development plans, including opportunities to contribute to thought leadership (blogs, talks, open-source contributions, internal workshops).
• Demonstrated experience leading multidisciplinary analytics/product/technical organisations through managers and senior leads, with evidence of building autonomous leaders rather than personally owning delivery.
• Cross-Functional Collaboration and Stakeholder Management.
• Partner with: Product (Sigma), Product Data Science, Engineering, Markets and Commercial.
• Drive alignment across: Roadmap, Ownership, delivery expectations.
• Act as the primary technical product partner for local Product, Commercial, Markets, and Strategy leaders on your products.
• Partner with key stakeholders - aligning on model requirements, productionisation timelines, performance targets, and integration roadmaps for ML-powered features.
• Drive cross-functional alignment - facilitate product councils, architecture reviews, roadmap syncs, and sprint demos to ensure all teams are rowing in the same direction.
• Communicate complex technical concepts in simple, business-friendly language to senior, non-technical stakeholders - building confidence, driving adoption, and securing buy-in for investment decisions.
• Represent DnA and MiQ in internal and external forums (Ex: product councils, client meetings, industry events) as a senior technical product leader.
• Cost, Risk and Operational Excellence.
• Own compute and tooling budgets for your domain; drive optimisation initiatives without compromising quality or innovation.
• Champion effective, lightweight Agile practices across teams; partner with Program/Project Management to continuously improve ways of working and delivery predictability.