Tech Mahindra: Data and Artificial Intelligence Interview Guide
Tech Mahindra's Data and AI Service Line decides which data and Artificial Intelligence (AI) deals the company pursues, how those deals are solved, and how the solutions are delivered to global enterprise clients. Interns here work on live pursuits, partner programs and client projects alongside senior leaders. Strong performers can earn a Pre-Placement Offer (PPO).
This guide is for MBA, PGDM and B.Tech students with prior data or technology experience who are preparing for this internship. It covers the four role tracks, every listed skill and responsibility, and the likely interview rounds. It also includes 29 practice questions with model answers, a four-week plan and the career path after a PPO.
1. About the Data and Artificial Intelligence Role
This is a business-and-technology internship split into four tracks. Depending on your track, you might prepare CXO (C-suite executive) review packs or write sections of a Request for Proposal (RFP) response. You might also build a Proof of Concept (PoC), plan Quarterly Business Reviews (QBRs) with cloud partners, or analyse data inside a live client project. Your output feeds real decisions on deals, partners and delivery.
You sit inside the Data and AI Service Line, which runs Delivery, Practice Sales, Alliances, Marketing, Operations, Learning and Development, and Innovation for clients across the US, Europe and Asia Pacific. Each day you work with your mentor, pursuit and delivery leads, partner managers and, in the Growth Office, the Service Line Head. For company background, read this Tech Mahindra corporate profile.
2. Required Skills and Qualifications
Educational Qualifications
Experience and Eligibility
Skills Overview
3. Day-to-Day Responsibilities
A typical week mixes track-specific work, such as a proposal section or a partner tracker, with a fixed rhythm of mentor check-ins and leadership reviews. The responsibilities below are grouped by track, followed by those every intern shares regardless of track.
Strategy and Growth Office
Drive Unit-Wide Programs
You work beside the Service Line Head on programs that cut across the whole unit, such as launching a new GenAI offering or a capability drive in one industry. In practice, you build the program plan, set check-ins with each owner and merge their updates into one view. You also flag a slipping workstream early, before the head has to ask.
Close CXO Office Initiatives
Asks from the CXO offices or the Service Line Head often arrive as a single line in a meeting or an email. You log each one with an owner, a due date and a status, and follow up every week. An item is marked closed only when there is proof, such as an approved deck, a launched offering or a signed partner agreement.
Run Strategy and Competitive Intelligence
You watch what rivals such as Accenture, TCS, Infosys, Wipro, HCLTech and Cognizant announce in data and AI, including new platforms, acquisitions, partnerships and large deal wins. You turn this into a short weekly note that answers one question for leadership: what should change in our offerings, pricing or target accounts because of it?
Prepare CXO Review Packs
Weekly and monthly CXO reviews run on a pack that covers pipeline, delivery risks, initiative status and the decisions leadership needs to make. You gather inputs from leaders, reconcile numbers that do not match across sources, and build the slides and pre-read. During the meeting, you record decisions and action items so the next review starts from them.
Track Leader Performance
You maintain the performance view for leaders across Delivery and Market Makers. It typically covers measures such as bookings, pipeline, utilization and client satisfaction. Each cycle you refresh the data, check it with each leader's team and highlight who is ahead of or behind plan. You add a one-line reason beside each number so the Service Line Head sees the story behind it.
Track AHMs and Team Communication
You track All-Hands Meetings (AHMs) and wider team communication for the unit. This covers drafting agendas, collecting leader updates and preparing slides. You also make sure key messages, such as new wins or organisation changes, reach every team, and you log the questions raised so leaders can respond afterwards.
Data and AI Presales and Solutioning
Support Large Deal Pursuits
You join the pursuit team from the first client conversation through to the final proposal. Day to day, you take notes in discovery calls, keep the pursuit calendar and client question log current, and remind section owners of deadlines. Your job is to make sure nothing the client asked for is missing from the final submission.
Requirement Analysis and Solution Write-Ups
When an RFP or a Request for Information (RFI) arrives, you break it into a compliance matrix that lists every client requirement and who will answer it. You then draft solution sections, for example how the team would migrate a bank's regulatory reporting to a cloud lakehouse. The writing has to be plain enough for a client evaluator to score quickly.
Executive Summaries and Pricing Inputs
You draft the executive summary, the two pages a client CXO actually reads. You also gather pricing inputs such as team size, roles, effort by phase and key assumptions. You do not set the final price, but you build the Excel effort sheet the pricing team relies on, so every number must be traceable.
Build Decks, POVs and Demo Storylines
You create client-ready decks, Point of View (POV) papers and demo storylines across data modernization, analytics, GenAI and agentic AI. A typical task is a ten-slide POV on how an insurer can use an AI agent to triage claims. It comes with a demo script showing the agent reading a claim, checking policy rules and routing it to the right team.
Research Context to Shape Win Themes
Before writing starts, you research the client's annual report, recent leadership statements, industry pressures and likely competitors. You turn this into three or four win themes, the reasons this client should choose Tech Mahindra. One example is faster time to value through reusable accelerators. These themes then run through every section of the response.
Prototype PoCs and Demos
You help build small working prototypes on hyperscaler services, data platforms and AI tools. That could be a question-answering assistant over sample product manuals built with a cloud-hosted Large Language Model (LLM). It could also be a notebook showing cleaned sales data feeding a forecast. Either way, the client sees the idea working rather than just described.
Maintain the Solution Asset Repository
You keep the library of case studies, client credentials and reusable solution assets current and easy to search. When a deal team needs three retail data modernization references by tomorrow, you find them and check they are cleared for external use. You then tailor them to the new pursuit.
Create Collaterals with AI
You use AI tools to speed up the writing of case studies, brochures, flyers and technical responses in question-and-answer format. The real skill is prompting well and then fact-checking and editing the draft. The final version must be accurate, on-brand and free of confidential client details, which sharpens your technical writing over time.
Data and AI Alliances
Build and Run the Partner Ecosystem
You help build and run relationships with hyperscalers, data platform companies and AI vendors. In practice, you keep partner contact maps current, prepare briefing notes before partner calls and track joint commitments. The aim is for each relationship to produce real opportunities, not just a logo on a slide.
Track Programs, Certifications, Incentives and Co-Sell
Each partner runs programs with tiers, certification targets, incentives and co-sell rules. You track how many engineers hold each certification, which incentives the unit qualifies for and which opportunities are registered for co-sell. This tells the alliance lead where the unit stands and what to push before a program deadline.
Partner Business Plans and QBR Material
You prepare partner business plans covering target accounts, joint offerings, certification goals and pipeline targets. Every quarter, you build the QBR deck that compares plan with actual results and sets the asks for the next quarter. The same deck serves internal leaders and the partner's team.
Run Joint Go-To-Market Campaigns
You help plan joint go-to-market (GTM) campaigns with partners, such as a webinar series on GenAI for manufacturers co-hosted with a cloud provider. You draft the campaign brief, coordinate content with Marketing and the partner, and track the leads generated. That way, the campaign is judged on pipeline, not attendance.
Map Partner Offerings to Solutions and Accounts
You map what each partner sells to the Service Line's solutions and priority accounts. For example, if a client has standardised on one cloud, you identify which of that partner's AI services pair with the unit's offerings. Account teams then walk into meetings with a joint story already prepared.
Coordinate Partner Enablement and Events
You coordinate enablement, such as partner-led training and certification drives for engineers, along with joint events and conference appearances. This means scheduling sessions, tracking attendance and certification completion, and handling logistics with the partner team. Missed certification targets can cost the unit program benefits, so this tracking matters.
Support Joint Account Planning
You support joint account planning sessions where Tech Mahindra and a partner agree which client opportunities to pursue together. You prepare the account view, including current spend, open opportunities and decision makers. Afterwards, you capture agreed actions and owners and follow up so both sides deliver what they committed.
Monitor Partner and Competitor Moves
You track partner announcements, new AI services and program changes, plus what competitors announce with the same partners. You summarise the implications in a short note. One example is a new hyperscaler agent service that overlaps with an accelerator the unit sells. You also suggest how the Service Line should respond.
Data and AI Delivery: Business and AI Analyst
Work Inside Live Client Engagements
You join live client projects and help turn a business problem into a working data or AI solution. One example is high subscriber churn at a telecom operator. You attend client calls, learn how the client's business actually runs and support the team from discovery through to go-live.
Document Requirements, Use Cases and Acceptance Criteria
You run or support workshops with client teams, then document business requirements, use cases and acceptance criteria. A good acceptance criterion is testable. For example: the loan-application dashboard refreshes daily by 8 am and shows approval rates by branch. Vague criteria lead to disputes at sign-off, so precision here protects the project.
Analyse Data and Build Dashboards
You explore client data in SQL, Excel or Python, check its quality and build dashboards that managers use. A logistics client, for instance, might need a view of delivery delays by hub and route, so operations heads can see where backlogs build up each morning.
Support Model and GenAI Use-Case Development
You support data scientists and engineers by preparing data, testing outputs and documenting results. For a GenAI assistant, this might mean building a test set of 100 real user questions and scoring each answer for accuracy and tone before the client pilot. That evidence decides whether the use case moves forward.
Track Delivery Health
You track milestones, risks, utilization and quality metrics for the engagement. Utilization is billable hours divided by available hours, so you can spot early when a team is underused or overloaded. You also maintain a risk log where each risk has an owner, a mitigation and a review date.
Prepare Status Reports and Governance Material
You prepare weekly status reports and steering committee packs for client and internal reviews. Each pack covers progress against plan, risks, decisions needed and next steps. The goal is a pack that lets a client sponsor make a decision in minutes rather than asking for another meeting.
Contribute to Accelerators and IP
When you solve something reusable, such as a data quality checklist or a prompt library for contract summarisation, you package it for the delivery practice. These accelerators and intellectual property (IP) assets make future projects faster. They also strengthen proposals, because the pursuit team can show working assets instead of promises.
Responsibilities Common to All Tracks
Own One Deliverable End to End
You receive one defined deliverable, such as a review pack, a proposal section, a partner plan or an analytics module, and own it from scoping to sign-off. Agree the scope and deadline in week one, and break the work into weekly milestones. Closing it on time and to standard is the clearest evidence you can offer for a PPO.
Turn Raw Inputs into Executive Output
You take messy inputs such as call notes, spreadsheets exported from different systems and long partner emails. You turn them into decks, dashboards, briefs and trackers a leader can use without edits. In practice, that means headline-style slide titles, consistent numbers across pages and one clear ask per page.
Run a Weekly Mentor Cadence
Each week you meet your mentor to cover the plan, progress, blockers and learnings. Bring a written one-page update with specific asks, such as an introduction to a delivery lead or feedback on a draft. This makes the session productive and shows you are driving your own internship.
Bring Data-Backed Recommendations
In team discussions, go beyond summarising what happened. Bring a number, a comparison or a trend, along with a recommendation. For example, you might suggest which two partners deserve focus next quarter based on co-sell pipeline and certification gaps, and explain what the unit would gain.
Collaborate Across Teams to Close Open Items
Open items often sit between Delivery, Sales, Alliances and Marketing, with no one owning them. You find the right owner, follow up politely and confirm closure. A common example is getting a case study approved by the delivery lead and formatted by Marketing before a pursuit deadline.
Present a Final Project to Leadership
At the end of the program, you present your internship project to Service Line leadership. Treat it like a client pitch: state the problem clearly, show your analysis, quantify the outcome you delivered and recommend what should happen next. This presentation weighs heavily in PPO decisions, so rehearse it with your mentor first.
4. Key Competencies for Success
Most shortlisted candidates know the vocabulary of data and AI. The ones who convert are those who think like a commercial partner to senior leaders, linking every idea to a client outcome, a deal or a partner.
5. Interview Process at Tech Mahindra
Campus hiring for consulting-style technology internships at large IT services firms usually runs in four to five stages. The exact mix depends on the campus and the track. Prepare for the sequence below and confirm the details with your placement cell once the process is announced.
Application and CV Shortlisting
The recruiting team screens CVs shared through the placement cell for academic consistency, no active backlogs and relevant data, analytics or technology experience. A CV that links past work to one of the four tracks, with measurable outcomes, stands out.
Online Assessment or Group Discussion
Some campuses add an aptitude and analytics test or a group discussion on a technology-business topic, such as GenAI adoption in Indian enterprises. This round tests structured thinking, clarity and the ability to build on other people's points rather than talk over them.
Functional and Technical Interview
This round is usually run by Data and AI practice members. Expect questions on data platforms, BI, ML, GenAI and agentic AI, and a deep dive into your CV projects. Delivery and Presales candidates may get a SQL, Python or Excel exercise.
Case or Leadership Round
A senior leader gives you a short business case, such as structuring an RFP response, diagnosing a falling win rate or planning a partner campaign. They assess how you structure ambiguity, whether you lead with a recommendation, and how you hold up under follow-up questions.
HR and Fit Discussion
An HR representative confirms your availability for the full duration, your openness to relocation and your motivation for Tech Mahindra. Expect questions about long-term interest in the IT services sector, since the internship is designed as a route to a PPO.
6. Interview Questions
Use STAR (Situation, Task, Action, Result) for behavioural questions, an answer-first structure for cases, and think aloud on technical questions so the interviewer can follow your logic.
Tech Mahindra interviewers for this role care less about textbook definitions and more about whether you can connect a concept to a client outcome, a deal or a partner. The technical block is the largest because that is where most candidates lose marks.
