Professional Overview
15+ years of experience in software development, cloud computing, data science, and AI-driven innovation, including 8+ years in senior leadership roles. Proven ability to align technology strategies with business objectives, manage large cross-functional teams, and deliver scalable, data-driven, and cloud-native solutions that enable digital transformation. Recognized for leading multimillion-dollar global projects, driving MarTech modernization (CDP, CRM, MDP), and building enterprise-grade distributed systems across AWS, Azure, and GCP. Adept at mentoring diverse technical teams—Data Engineers, Data Scientists, BI Analysts, DevOps Engineers, and Automation Experts—to achieve measurable business outcomes. Key Achievements: Spearheaded Gen AI and Data Science initiatives, including AI chatbots, LLM-based personalization, and predictive analytics frameworks that enhanced marketing and customer engagement.Led cross-functional teams to design and implement Customer Data Platforms (CDP) and real-time data ecosystems, enabling intelligent segmentation, marketing automation, and improved conversion rates.Architected scalable, distributed data systems and cloud infrastructures supporting enterprise data lakes, ML pipelines, and advanced analytics.Championed innovation in MarTech, Data Engineering, and Cloud Architecture, establishing best practices for automation, cost optimization, and performance at scale.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
data science & analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
