Associate Director, Analytics - Construction, California

Role Brief:

We are seeking a highly versatile and client-facingAssociate Director, Analytics to drive AI and analytics transformation initiatives for strategic clients in the construction and built-environment domain. This role blends the responsibilities of a product owner, analytics consultant, solution architect, and hands-on technology leader.

The ideal candidate is someone who began their career as a strong hands-on engineer/coder and has evolved into a consulting-led leadership role capable of owning business outcomes, shaping AI products, engaging senior stakeholders, and leading cross-functional delivery teams.

This individual will work at the intersection of AI/ML and analytics strategy, construction domain workflows and operational intelligence, product ownership and stakeholder management, data engineering and application architecture and full-stack AI solution delivery.

The role requires both strategic thinking and technical depth, with the ability to translate ambiguous business problems into scalable AI-enabled products and platforms.

Responsibilities:

• Act as the primary AI/Analytics Product Owner for client engagements within the construction domain.
• Partner with client business stakeholders to identify high-value AI, analytics, automation, and optimization opportunities.
• Define product vision, roadmap, KPIs, feature prioritization, and release planning for AI-enabled platforms and solutions.
• Drive discovery workshops, problem framing sessions, and use-case prioritization exercises.
• Translate business problems into scalable data, analytics, and AI solution architectures.
• Own stakeholder communication, executive reporting, and strategic advisory discussions.
• Lead development of AI/ML-driven solutions involving Computer Vision, OCR/document intelligence, LLM and GenAI applications, Predictive analytics, Operational optimization, Recommendation systems
• Define AI solution strategy, experimentation approach, evaluation metrics, and product ionization plans.
• Guide teams on model selection, data strategy, feature engineering, and deployment approaches.
• Establish scalable AI governance, monitoring, and feedback-loop mechanisms.
• Provide technical leadership across:
  Data Engineering, Backend/API development, Full-stack application architecture, Cloud-native analytics platforms, BI and visualization ecosystems
• Collaborate with engineering teams to design scalable architectures and integration patterns.
• Review technical designs, APIs, pipelines, and engineering implementation approaches.
• Ensure alignment between product vision and technical execution.
• Act as a trusted advisor to client leadership teams.
• Lead requirement discussions, solution walkthroughs, demos, and steering committee updates.
• Drive cross-functional collaboration across business, data science, engineering, and UX teams.
• Manage delivery governance, prioritization, risks, dependencies, and execution tracking.
• Mentor teams and foster a strong engineering and innovation culture.

Requirements:

• 10-15+ years of experience across analytics, AI/ML, data engineering, and enterprise application delivery.
• Prior experience in consulting, analytics advisory, or client-facing transformation programs.
• Strong experience acting as AI Product Owner, Analytics Lead, Solution Architect, Technical Program Lead.
• Early career experience as a hands-on software engineer/developer is mandatory.
• Experience working with construction, engineering, manufacturing, industrial, or built-environment clients is strongly preferred.
• Knowledge of Analytics & AI.
• Strong understanding of Machine Learning, Deep Learning, GenAI/LLM ecosystems, NLP and Computer Vision, Predictive analytics, Statistical modelling.
• Experience with AI product lifecycle management and production AI systems.
• Strong knowledge of Data pipelines and ETL/ELT, Data warehousing/Lakehouse architectures, Streaming and batch processing, SQL and distributed data processing
• Experience with modern cloud data ecosystems.
• Strong backend engineering foundation with experience in Python / Node.js / Java, REST APIs and microservices, Event-driven systems
• Understanding of modern frontend and full-stack application architecture.
• Ability to…