Tata GenAI Powered Data Analytics

Why complete this Job Simulation

A risk-free way to experience work on the job with us at Tata. Practice your skills with example tasks and build your confidence to ace your applications.

Self-paced

3-4 hours

No grades

No assessments

Intermediate

Welcome to the GenAI Powered Data Analytics Job Simulation! We are thrilled to have you here.

Tata Insights and Quants (Tata iQ) is the Tata Group’s advanced analytics and AI center of excellence. Tata iQ partners with companies across the Group to turn data into competitive advantage by enabling smarter, data-informed decision-making.

During this program, you will step into the role of an AI transformation consultant and complete tasks that replicate the work this role does every day. You’ll learn key skills in:

Predictive modeling using GenAI tools
Data exploration and quality assessment
Business storytelling and recommendation design
Designing AI-driven systems for fair and responsible automation

We hope this program provides a great resource for you to upskill and strengthen your resume as you explore career options and a potential future at Tata iQ.

How it works

Complete tasks guided by pre-recorded videos and example answers from our team at Tata. No live sessions, all self-paced.
Earn a certificate and add it to your resume and LinkedIn as an extracurricular activity.
Stand out in applications. Confidently answer interview questions and explain why you’re a good fit for our team.

Skills you will learn and practice:

AI Analytics

AI Strategy

Analytical Reporting

Business Communication

Data Interpretation

Data Quality Management

Decision Making

Ethical Reasoning

Exploratory Data Analysis

Model Selection

Model Validation

Predictive Analytics

Process Automation

Regulatory Compliance

Strategic Thinking

Introduction from Tata

Tasks

Intro & Scenario

Background context and your project team

Your role

You are an AI transformation consultant at Tata iQ, specializing in data-driven decision-making for financial services.
You work within a larger data analytics team, collaborating with business leaders to develop AI-powered solutions.
Your team has been tasked with helping Geldium Finance, a financial services company, reduce its high credit card delinquency rate by performing advanced analytics and building AI/ML models with the assistance of GenAI.

Your goal

Your primary objective is to analyze customer data and predict delinquency risks using AI-driven techniques.
You will develop a recommendation framework to help the Head of Collections at Geldium determine the best intervention strategies for at-risk customers.
Throughout the project, you will ensure that AI-driven solutions are ethical, explainable, and effective in supporting responsible financial decision-making.

Intro & Scenario

Background context and your project team

Your role

You are an AI transformation consultant at Tata iQ, specializing in data-driven decision-making for financial services.
You work within a larger data analytics team, collaborating with business leaders to develop AI-powered solutions.
Your team has been tasked with helping Geldium Finance, a financial services company, reduce its high credit card delinquency rate by performing advanced analytics and building AI/ML models with the assistance of GenAI.

Your goal

Your primary objective is to analyze customer data and predict delinquency risks using AI-driven techniques.
You will develop a recommendation framework to help the Head of Collections at Geldium determine the best intervention strategies for at-risk customers.
Throughout the project, you will ensure that AI-driven solutions are ethical, explainable, and effective in supporting responsible financial decision-making.

Reviews

4.6

I liked how the simulation provided practical experience in using GenAI for data analysis, predicting customer delinquency, and developing AI-driven business recommendations. It also helped me understand the importance of fairness, explainability, and responsible AI in financial decision-making. The real-world business scenarios made the learning experience engaging and valuable.

Student, University of Mumbai

I really appreciated how realistic and well-structured the tasks were. Connecting exploratory data analysis and predictive modeling directly to real-world business strategy and executive stakeholder presentations made the experience incredibly practical. It provided great hands-on insight into how data science and AI are applied to solve strategic challenges in the financial sector.

Student, University of Calicut

Bridging Analytics to Business Strategy: Translating raw exploratory data analysis (EDA) and predictive risk scores (Task 1 & Task 2) into a concise, two-page stakeholder report for Geldium’s Head of Collections (Task 3) mirrors real boardroom expectations—focusing on actionable SMART recommendations rather than just model accuracy metrics.

Student