Data Analyst AI Developer

Role & responsibilities The Data Analyst / AI Developer will be responsible for: Building enterprise AI applications Developing predictive analytics models Implementing Generative AI solutions Building AI agents Supporting strategic decision making through analytics Working closely with product teams to embed AI capabilities into software products Key Responsibilities Data Analytics Collect, cleanse and analyse structured and unstructured data. Design enterprise data warehouses and analytical models. Build executive dashboards and KPI reporting systems. Develop predictive and prescriptive analytics. Identify business trends and growth opportunities. Generate reports for executive management. Perform customer behaviour analysis. Conduct financial and operational data analysis. Prepare data visualizations using Power BI or equivalent BI platforms. Create data quality metrics and governance standards. Artificial Intelligence Development Develop AI solutions using: Large Language Models (LLMs) Retrieval Augmented Generation (RAG) AI Agents Natural Language Processing (NLP) Machine Learning Deep Learning Recommendation Engines Predictive Models Conversational AI Generative AI Design and implement: Enterprise AI Assistants Intelligent Search Platforms Document Intelligence Solutions AI-powered Customer Support AI Workflow Automation AI Code Generation Assistants AI-powered Banking Solutions AI-powered Compliance Systems Product Development Collaborate with product teams to integrate AI into: Core Banking Loan Origination Fraud Detection Credit Scoring Treasury Risk Management Customer Service Digital Banking Data Engineering Build scalable ETL pipelines. Design data lakes and data warehouses. Develop APIs for AI services. Integrate enterprise databases. Optimize SQL queries. Implement data governance standards. Ensure data security and privacy. AI Research Continuously evaluate emerging AI technologies including: OpenAI Azure AI Microsoft Copilot Anthropic Claude Google Gemini Open-source LLMs Agentic AI frameworks Vector Databases Knowledge Graphs Autonomous AI Agents Recommend adoption strategies aligned with business objectives. Preferred candidate profile Technical Skills The ideal candidate should possess hands-on experience with: Programming Python C# SQL JavaScript TypeScript .NET AI & Machine Learning TensorFlow PyTorch LangChain Semantic Kernel LlamaIndex Hugging Face Scikit-Learn Databases SQL Server PostgreSQL MySQL Development Tools Git Azure DevOps Docker Kubernetes Visual Studio VS Code Desired Functional Knowledge Experience in one or more of the following domains is desirable: Banking Financial Services Insurance Lending Digital Payments Manufacturing Aerospace Defence ERP CRM Enterprise SaaS Educational Qualifications Minimum: Bachelor's Degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Statistics, Mathematics or Engineering. Preferred: Master's Degree in AI, Data Science, Computer Science or Business Analytics. Experience Essential: 2 TO 4 years in Data Analytics, AI Development or Machine Learning. Preferred: Experience building enterprise AI solutions. Experience integrating AI into business applications. Experience with cloud-native AI platforms. Soft Skills Strong analytical thinking Excellent problem-solving ability Business acumen Strategic thinking Excellent communication skills Curiosity and continuous learning Ability to work directly with senior leadership High attention to detail Innovation mindset Strong presentation skills Perks and benefits