Role Objective: 

Lead the development of AI-driven data architecture, advanced analytics, and intelligent automation—leveraging modern cloud platforms—to power strategic decision-making, enhance customer experiences, and drive business growth. 

Key Responsibilities: 

• Design and maintain clean, scalable, AI-ready data pipelines using fundamentals of data engineering, ensuring robust data governance and archival processes. 
• Build and optimize data infrastructure across GCP and AWS, ensuring scalability, security, and performance. 
• Oversee the creation of Customer 360 intelligence platforms, integrating behavioral, transactional, and engagement data for unified insights. 
• Drive AI-powered predictive modeling (churn, LTV, activity scoring), recommendation engines, and automated product experimentation (A/B/n testing, dynamic pricing strategies). 
• Lead product analytics initiatives to measure feature adoption, user behavior, and product performance, feeding insights into business and product roadmaps. 
• Map and optimize customer journeys with real-time data insights, AI-based personalization, and automated interventions. 
• Champion data democratization by developing interactive dashboards, natural language query tools, and self-service analytics powered by generative AI. 
• Collaborate with cross functional teams to deploy AI-driven automation—including conversational agents, sentiment analysis, and intelligent knowledge base enrichment. 
• Stay ahead of emerging AI and cloud technologies, evaluating their application across business units. 

Ideal Background: 

• 6–10 years in data science, data engineering, or AI strategy with proven leadership experience. 
• Strong expertise in machine learning for business applications, including generative AI, LLMs, and recommendation systems. 
• Hands-on experience with GCP, AWS, the modern data stack (dbt, Snowflake, Airflow, Looker, etc.), and AI tooling (LangChain, Vertex AI, Azure AI, etc.). 
• Proven track record in architecting and deploying end-to-end AI and analytics solutions that deliver measurable business impact. 
• Solid grasp of product analytics frameworks and methodologies. 
• Excellent communication skills to translate complex AI/data concepts into actionable strategies for non-technical stakeholders.