Senior Data Science & Advanced Analytics Leader

As a Senior Data Science & Advanced Analytics Leader, your main responsibility will be to drive data strategy, lead the design and development of scalable data solutions, and enable AI/ML-driven decision-making across the organization. You will oversee the end-to-end development lifecycle, manage high-performing teams, and collaborate closely with cross-functional stakeholders to enable data-driven product innovation and business impact. Key Responsibilities: - Lead the end-to-end architecture, development, and optimization of scalable data pipelines supporting AI/ML model deployment and analytics use cases. - Oversee Database and NoSQL data platforms (810+ years) including schema design, performance optimization, and data modeling for transactional and analytical workloads. - Provide strong expertise in ETL/ELT workflow orchestration, data integration, and quality frameworks. - Have hands-on experience working with Hadoop, Hive, and broader big data ecosystems for large-scale, high-volume data processing. - Drive the delivery of executive-level reporting, real-time dashboards, and self-service BI solutions, using tools such as Tableau or Power BI. - Define and execute product analytics strategy, enabling insights that power product direction and customer engagement. - Lead AI-based feature development from ideation to production-scale rollout. - Collaborate with engineering, product, business, and customer stakeholders to transform business objectives into measurable, data-driven outcomes. - Mentor and manage data engineers, BI developers, and data scientists, fostering a high-performance culture. Qualifications Required: - 10+ years of professional experience in Data Science, Advanced Analytics, or Business Intelligence. - Minimum 4+ years leading and managing high-performing data/analytics teams. - Proven experience with SQL/NoSQL databases, schema design, performance tuning, and optimization. - Strong working knowledge of Hadoop, Hive, and big data processing frameworks. - Demonstrated proficiency with Tableau or Power BI for rich data visualization and analytics. - Deep understanding of ETL processes, data transformation logic, and workflow management tools. - Experience deploying AI/ML-driven analytics solutions at scale. - Excellent communication and stakeholder management skills. The company prefers candidates with Cloud experience (AWS, Azure, GCP - Data Factory, Redshift, Databricks, BigQuery, or equivalent), experience with MLOps or DataOps frameworks, familiarity with containerization and CI/CD (Docker, Kubernetes, Jenkins), and knowledge of statistical analysis, predictive modeling, and feature engineering.,