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Banking Operation Analyst

Nttdata

  • Gurgaon, Haryana, India
  • 4.5 LPA
  • Fresher (0-1 Yrs)
  • Posted Today
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About the role

NTT DATA is a global IT services powerhouse with a strong footprint in India. With over 150,000 professionals worldwide, the company delivers end‑to‑end digital solutions across banking, finance, healthcare, and many other sectors. Its Indian operations, especially in Gurgaon, are known for a culture that blends cutting‑edge technology with deep domain expertise, enabling employees to work on large‑scale projects for Fortune‑500 clients while enjoying a supportive learning environment. NTT DATA’s commitment to continuous innovation, sustainability, and inclusive growth makes it a preferred employer for fresh graduates looking to launch a career in the financial services domain. The Banking Operation Analyst role sits within the BPO arm of NTT DATA and focuses on Joint Recovery Processing and Chargeback Management. Reporting to the Supervisor of Joint Recovery Processing, the analyst will handle fraud and dispute cases, ensure compliance with card association rules, and perform data‑driven analysis to identify fraud trends. The position is full‑time, office‑based in Gurgaon, and follows a rotational evening shift schedule, offering exposure to real‑time financial operations and cross‑functional collaboration. **Key Responsibilities** 1. Analyze and process fraud/dispute cases using the TDR case management system while meeting internal SLAs. 2. Manage the complete chargeback lifecycle across first, second, and third cycles, including retrieval requests, merchant challenges, and representment decisions. 3. Conduct proactive investigations of potential fraud cases and coordinate with law‑enforcement agencies when required. 4. Generate trend reports on fraud types and communicate findings to the fraud strategy team. 5. Ensure strict adherence to PCI‑DSS standards, association regulations, and departmental escalation procedures. 6. Perform data‑analysis using Excel and other analytical tools to identify patterns and support decision‑making. 7. Mentor new hires on chargeback processes, system navigation, and best practices. 8. Maintain high‑quality customer interactions, handling conflict with composure and professionalism. 9. Participate actively in team meetings, coaching sessions, and continuous improvement initiatives. 10. Document case details accurately for audit and compliance purposes. **Tech Stack & Tools**: Microsoft Office Suite (Word, Excel, PowerPoint), TDR/TS2 case management platforms, PCI‑DSS compliance tools, basic data‑visualisation utilities, and French language proficiency for multilingual communication. **Growth Path**: Starting as a Banking Operation Analyst, high performers can progress to Senior Analyst, Team Lead, Operations Manager, and eventually to specialized roles in Risk Management or Credit Card Operations. NTT DATA offers structured learning programs, certifications, and internal mobility across its global network. **Why Join NTT DATA?** The company provides a stable, globally recognized brand, exposure to large‑scale banking operations, and a culture that encourages upskilling and mentorship. Freshers gain hands‑on experience with industry‑standard processes, access to continuous learning platforms, and a clear career trajectory within a supportive, inclusive environment.

Eligibility & process

Who can apply

Bachelor’s degree in Finance, Business Administration, Economics or related field; Minimum 60% aggregate (or CGPA 6.0/10); Graduating batch 2024‑2026; No active backlogs at the time of joining; Proficiency in English and French is preferred.

Skills & stack

Fraud Analysis Chargeback Processing Microsoft Excel Microsoft Word Powerpoint Data Analysis Pci‑Dss Compliance French Language

Selection process

  1. Round 1: Online aptitude test (logical reasoning, quantitative, English)
  2. Round 2: Technical interview focusing on fraud, chargeback concepts and case studies
  3. Round 3: HR interview assessing cultural fit, communication skills and career aspirations

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Fraud Analysis, Chargeback Processing, Microsoft Excel, Microsoft Word, Powerpoint, Data Analysis, Pci‑Dss Compliance, French Language) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Nttdata Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Nttdata as a Banking Operation Analyst?
Highlight Nttdata's market reputation, recent tech innovations, and how your skills in Fraud Analysis directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Nttdata 4.5 LPA
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