AI Data Analytics and Automation Lead

As a Senior AI Data Analytics and Automation Lead, you will help transform business operations through data-driven insights, intelligent automation, and AI-powered solutions. You will partner with business and technology leaders to develop scalable reporting platforms, automate complex workflows, and deploy modern AI capabilities that improve decision-making, efficiency, and organizational productivity.

You will combine expertise in analytics, data engineering, automation, and Generative AI to design solutions that convert business challenges into measurable outcomes. Your work will influence strategic decisions across the organization and accelerate the adoption of AI-enabled business processes. Responsibilities Analytics and Business Intelligence

• Design, develop, and maintain executive dashboards and enterprise reporting solutions using Power BI.
• Create scalable KPI frameworks and operational reporting models that support business performance management.
• Transform complex datasets into actionable insights through advanced analytics and data visualization.
• Develop analytical models and reporting solutions using Excel and other business intelligence tools.
• Partner with stakeholders to define metrics, reporting requirements, and success measures.

Data Engineering and Automation

• Build and maintain Python-based automation solutions for reporting, reconciliation, data transformation, and process optimization.
• Develop and manage ETL/ELT pipelines that integrate data across multiple enterprise systems.
• Automate recurring business processes to improve efficiency, scalability, and data quality.
• Implement data governance, monitoring, and quality-control frameworks to ensure trusted business reporting.

AI and Intelligent Automation

• Identify opportunities to apply Generative AI and agentic AI technologies to business operations.
• Design and deploy AI-powered assistants, workflow automations, and decision-support solutions.
• Build solutions leveraging LLMs, RAG architectures, vector databases, prompt engineering, and AI orchestration frameworks.
• Evaluate emerging AI technologies and recommend scalable enterprise adoption strategies.
• Partner with technical and business teams to operationalize AI capabilities across the organization.

Leadership and Stakeholder Engagement

• Collaborate with senior executives and business leaders to align analytics and AI initiatives with strategic priorities.
• Present insights, recommendations, and implementation roadmaps to executive audiences.
• Serve as a trusted advisor on data analytics, automation, AI strategy, and best practices.
• Drive adoption of data-driven decision-making and intelligent automation across the organization.

• Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Analytics, or a related technical field, or equivalent practical experience.
• 5 years of experience in business intelligence, data analytics, data engineering, automation, or related disciplines.
• Experience developing enterprise reporting solutions using Power BI, including data modeling, DAX, Power Query, and dashboard optimization.
• Experience with Python for analytics, automation, API integration, and workflow orchestration.
• Experience working with SQL and large-scale enterprise data platforms.
• Experience engaging with business stakeholders to translate requirements into analytical and technology solutions., * Master’s degree in a technical or quantitative field.
• Experience with Generative AI, Large Language Models (LLMs), and intelligent automation solutions.
• Experience with agentic AI frameworks, including Microsoft Copilot Studio, LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or Google Agent Development Kit (ADK).
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures, vector databases, prompt engineering strategies, and AI evaluation frameworks.
• Experience with cloud technologies including Google Cloud Platform (Google Cloud Platform), Microsoft Azure, or Amazon Web Services (AWS).
• Experience leading analytics and automation initiatives within financial services, operations, or large enterprise environments.