Data and AI Analyst

Summary

As a Data Analyst, you will play a critical role in driving informed decision making processes by analyzing complex data sets and transforming raw data into actionable insights. The ideal candidate should have worked in the banking domain and possess a strong analytical mindset, exceptional problem solving capabilities, and a solid understanding of financial metrics. The candidate should have data migration experience. Your responsibilities will include developing and maintaining dashboards, conducting in depth market research, performing trend analysis, and collaborating with cross functional teams to ensure data integrity. This role requires strong proficiency in data visualization tools, statistical analysis software, and the ability to communicate findings effectively to stakeholders. Additionally, the role increasingly involves leveraging modern AI/ML techniques to enhance data insights and automation.

Responsibilities

• Lead data migration activities and analysis
• Work with Data scientists/Business Analysts/Product Owners to understand MI and dashboard requirements
• Design Data Solutions: Leverage your analytical skills to design innovative data solutions that address complex business requirements and drive decision making
• Create detailed field level mappings as needed for different MI Dashboards
• Develop and maintain comprehensive dashboards to visualize key performance indicators
• Conduct market research and trend analysis to inform strategic business decisions
• Collaborate with cross functional teams to ensure data accuracy and integrity
• Identify and recommend process improvements based on data analysis findings
• Prepare detailed reports and presentations on analytical findings for stakeholders
• Stay updated on industry trends, data analysis techniques, and best practices

Requirements

• Minimum of 8+ years of experience in data engineering or a similar role
• Technical Proficiency: Strong Python skills for data analysis and software development, familiarity in libraries/frameworks such as PyTorch or TensorFlow
• AI Expertise: Hands on experience with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), vector databases, and prompt engineering
• Machine Learning Fundamentals: Understanding of classical ML algorithms, data preprocessing techniques, and model evaluation methods
• Frameworks: Experience with agentic and orchestration frameworks such as LangChain, AutoGen, or CrewAI
• Cloud & DevOps: Experience deploying data/ML solutions on cloud platforms (AWS, Azure, GCP) and working with MLOps tools such as Docker

Equal Opportunity Employer

NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.