Download free Goldman Sachs placement papers 2025 PDF with previous year questions and solutions. Access exam pattern, eligibility criteria, interview process, and complete preparation guide.
Goldman Sachs is a leading global investment banking, securities, and investment management firm. Founded in 1869, Goldman Sachs provides services to corporations, governments, and individuals. Goldman Sachs India has technology divisions working on trading systems, risk management, and financial technology, making it a sought-after employer for engineering graduates.
Headquarters: New York, USA
Employees: 45,000+ globally
Industry: Investment Banking, Financial Services
Revenue: $46+ Billion USD (2023)
Download free Goldman Sachs placement papers 2025 with previous year questions, detailed solutions, exam pattern, and complete preparation guide. Access Goldman Sachs last 5 years placement papers with solutions PDF download and practice with solved questions covering all sections.
Goldman Sachs eligibility criteria for freshers requires a minimum CGPA of 7.0 (70%) across all academic levels. Here’s the detailed breakdown:
Minimum CGPA Required
10th Standard: 70% or 7.0 CGPA minimum
12th Standard: 70% or 7.0 CGPA minimum
Graduation: 70% or 7.0 CGPA minimum (aggregate)
Important: You must meet the minimum CGPA requirement in ALL three levels (10th, 12th, and graduation) to be eligible for Goldman Sachs placement.
CGPA for Better Selection Chances
7.0-7.9 CGPA: Meets minimum requirement, eligible to apply
8.0-8.9 CGPA: Good chances of selection (average selected candidate range)
9.0+ CGPA: Excellent chances, combined with strong technical skills
Academic Requirements
Marks: 70% or 7.0+ CGPA in 10th, 12th, and graduation
Degree: B.Tech/B.E./M.Tech in Computer Science, IT, or related fields
Year of Study: Final year students and recent graduates (within 2 years)
Backlogs: No active backlogs at the time of application
Branch Eligibility
Eligible Branches: Computer Science, Information Technology, Electronics, Electrical, and related engineering branches
Programming Focus: Strong proficiency in Java, Python, or C++
Experience: Freshers and candidates with 0-2 years experience
Additional Criteria
Programming Skills: Strong fundamentals in data structures and algorithms
Gap Years: Maximum 2 years gap allowed with valid reason
Course Type: Full-time regular courses only
Nationality: Indian citizens and eligible international students
Analyst Role
Primary Role: Analyst (Technology)
Salary Package: ₹18-22 LPA for freshers
Selection: Through Goldman Sachs placement process (5 rounds)
Focus: Strong problem-solving, coding skills, and system design
Access free Goldman Sachs placement papers PDF and Goldman Sachs previous year question paper with detailed solutions. Download Goldman Sachs last year question paper and Goldman Sachs question paper PDF from previous years with comprehensive question banks covering coding problems, system design, and technical interviews.
2024 Placement Papers PDF
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2025 Placement Papers PDF
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2026 Preparation Guide
Prepare for Goldman Sachs placement 2026 with expected exam pattern, coding questions, and comprehensive preparation strategy.
What's Included
Complete Goldman Sachs placement papers (2024-2026) with coding questions, detailed solutions, answer keys, exam pattern analysis, and topic-wise organization.
Preparation Guide
Complete guide on how to prepare for Goldman Sachs placement papers with study plans, round-by-round strategy, and tips.
Interview Experience
Read authentic Goldman Sachs placement interview experiences from recent candidates with real questions and tips.
HR Interview Questions
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Campus Recruitment
Primary Method: Through college placement cells during campus drives
Process: College placement office coordinates with Goldman Sachs recruitment team
Online Application
Direct Application: Apply through Goldman Sachs careers portal
Process: Submit resume and complete online application form
Referral Program
Employee Referral: Get referred by current Goldman Sachs employees
Process: Employee submits referral through internal portal
The Goldman Sachs placement process focuses on technical excellence and problem-solving ability. Understanding the detailed exam pattern is crucial for effective preparation.
Online Assessment (OA) - 90 minutes
Total Duration: 90 minutes Total Questions: 2-3 coding problems + mathematical aptitude Format: Online coding platform Negative Marking: No Platform: HackerRank or similar
Section-wise Breakdown:
| Section | Questions | Time | Difficulty | Focus Areas |
|---|---|---|---|---|
| Coding Problems | 2-3 | 60-70 min | Medium-Hard | Arrays, Strings, DP, Graphs |
| Mathematical Aptitude | 5-10 | 20-30 min | Medium | Probability, Statistics, Quantitative |
Section Details:
Important Notes:
Success Rate: ~15-20% of candidates clear this round
Technical Interview Round 1 - 45 minutes
Format: Virtual/Onsite Total Problems: 2-3 coding problems Language: C++, Java, Python Time: 45 minutes
Problem Types:
Passing Criteria: Solve at least 2 problems optimally with clear explanation
Evaluation:
Success Rate: ~40% of OA candidates advance
Technical Interview Round 2 - 45 minutes
Format: Virtual/Onsite Focus Areas: System design, technical deep dive, projects Time: 45 minutes
Topics Covered:
Evaluation:
Success Rate: ~50% of Round 1 candidates advance
Managerial Round - 45 minutes
Format: Virtual/Onsite Focus: Behavioral questions, technical discussion, leadership Time: 45 minutes
Topics Covered:
Evaluation Criteria:
Success Rate: ~60% of Round 2 candidates advance
HR Interview - 30 minutes
Format: Virtual/Onsite
Success Rate: ~80% of Managerial Round candidates get offers
| Phase | Duration | Key Activities |
|---|---|---|
| Application & Screening | 1 week | Resume screening, initial assessment |
| Online Assessment | 1-2 days | Coding test and aptitude |
| Technical Interviews | 1 week | Round 1 and Round 2 technical interviews |
| Managerial Round | 2-3 days | Behavioral and leadership assessment |
| HR Interview | 1-2 days | Final discussion and offer negotiation |
| Result Declaration | 3-5 days | Offer letter and onboarding details |
Practice with Goldman Sachs placement paper questions from previous years. These questions cover coding problems, system design scenarios, and technical concepts commonly asked in Goldman Sachs interviews.
Q1: Find Maximum Profit from Stock Prices
Problem: Given an array of stock prices, find the maximum profit you can make by buying and selling at most twice.
Solution:
def maxProfit(prices): if not prices: return 0
# First transaction: buy and sell profit1 = 0 min_price = prices[0] for price in prices: min_price = min(min_price, price) profit1 = max(profit1, price - min_price)
# Second transaction: buy and sell profit2 = 0 max_price = prices[-1] for i in range(len(prices)-1, -1, -1): max_price = max(max_price, prices[i]) profit2 = max(profit2, max_price - prices[i])
return profit1 + profit2Explanation: Use dynamic programming approach. First pass finds maximum profit from one transaction, second pass finds maximum profit from second transaction starting from the end.
Time Complexity: O(n)
Space Complexity: O(1)
Q2: Design a Low-Latency Trading System
Problem: Design a system that can process 1 million trades per second with latency < 1ms.
Solution:
Explanation: Low-latency systems require in-memory processing, minimal network hops, and optimized data structures. Event-driven architecture allows parallel processing.
Key Components: Message queue, in-memory cache, time-series database, load balancer
Q3: Implement LRU Cache
Problem: Design and implement a data structure for Least Recently Used (LRU) cache with O(1) time complexity for get and put operations.
Solution:
class Node: def __init__(self, key, val): self.key = key self.val = val self.prev = None self.next = None
class LRUCache: def __init__(self, capacity): self.capacity = capacity self.cache = {} self.head = Node(0, 0) self.tail = Node(0, 0) self.head.next = self.tail self.tail.prev = self.head
def get(self, key): if key in self.cache: node = self.cache[key] self._remove(node) self._add(node) return node.val return -1
def put(self, key, value): if key in self.cache: self._remove(self.cache[key]) node = Node(key, value) self._add(node) self.cache[key] = node if len(self.cache) > self.capacity: lru = self.tail.prev self._remove(lru) del self.cache[lru.key]
def _add(self, node): node.prev = self.head node.next = self.head.next self.head.next.prev = node self.head.next = node
def _remove(self, node): node.prev.next = node.next node.next.prev = node.prevExplanation: Use doubly linked list for O(1) insertion/deletion and hash map for O(1) lookup. Move accessed items to front, remove from tail when capacity exceeded.
Time Complexity: O(1) for both operations
Q4: Design a Risk Management System
Problem: Design a system to monitor and manage financial risk in real-time for trading operations.
Solution:
Explanation: Risk management requires real-time processing, historical analysis, and alerting. System must handle high throughput and provide low-latency risk calculations.
Learn from real Goldman Sachs placement interview experiences shared by candidates who successfully cleared the placement process. These authentic stories help you understand what to expect and how to prepare effectively.
Key Insights from Interview Experiences:
Complete Interview Experiences
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Data Structures
Arrays & Strings: Manipulation, searching, sorting algorithms
HashMaps: Hash tables, collision handling, applications
Trees: Binary trees, BST, AVL trees, tree traversals
Graphs: Graph representation, BFS, DFS, shortest paths
Advanced: Tries, segment trees, Fenwick trees
Algorithms
Dynamic Programming: Memoization, tabulation, optimization problems
Greedy Algorithms: Activity selection, scheduling, optimization
Graph Algorithms: Dijkstra, Bellman-Ford, topological sort
Sorting & Searching: Quick sort, merge sort, binary search
String Algorithms: KMP, Rabin-Karp, suffix arrays
System Design
Low-Latency Systems: In-memory processing, event-driven architecture
Distributed Systems: Load balancing, consistency, CAP theorem
Database Design: Normalization, indexing, query optimization
Caching Strategies: Multi-level caching, cache invalidation
Scalability: Horizontal scaling, microservices, message queues
Prepare for Goldman Sachs placement HR interview with common questions and effective strategies. Goldman Sachs HR interview focuses on cultural fit, career goals, and alignment with company values.
Common HR Interview Topics:
Complete HR Interview Guide
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Key Preparation Principles:
Preparation Approaches:
Complete Preparation Guide
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| Level | Experience | Base Salary | Total Package | Typical Background |
|---|---|---|---|---|
| Analyst | 0-1 years | ₹15-18 LPA | ₹18-22 LPA | New graduates |
| Associate | 1-2 years | ₹20-25 LPA | ₹25-30 LPA | 1-2 years experience |
| Vice President | 3-5 years | ₹35-45 LPA | ₹40-50 LPA | Senior engineers |
| Managing Director | 5+ years | ₹50+ LPA | ₹60+ LPA | Leadership roles |
| Role | Level | Total Package | Requirements |
|---|---|---|---|
| Quantitative Analyst | Entry | ₹20-25 LPA | Strong math/statistics background |
| Risk Analyst | Entry | ₹18-22 LPA | Finance/risk management knowledge |
Hiring Trends 2025
Increased Focus on System Design: More emphasis on designing scalable, low-latency systems
AI/ML Integration: Growing demand for candidates with AI/ML experience in financial technology
Cloud Technologies: Increased focus on cloud-native architectures and microservices
Process Changes
Virtual Interviews: Continued use of virtual interview platforms for all rounds
Behavioral Assessment: Earlier assessment of behavioral fit in the process
Technical Depth: Deeper technical discussions in system design rounds
New Initiatives
Campus Ambassador Program: Student ambassadors help with recruitment
Hackathons: Regular hackathons for identifying talent
Internship Programs: Strong internship-to-full-time conversion pipeline
Company Growth
Technology Expansion: Growing technology teams in India (Mumbai, Bangalore)
Digital Transformation: Focus on digital banking and fintech solutions
Innovation Labs: New innovation centers for cutting-edge technology development
Goldman Sachs placement papers are previous year question papers from Goldman Sachs recruitment tests and interview rounds. These papers contain coding problems, system design questions, technical interview questions, and behavioral questions that help students understand the exam pattern and prepare effectively for Goldman Sachs placement process.
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Yes, you can access Goldman Sachs placement papers online with previous year coding questions, technical interview questions, and solutions. Our website provides Goldman Sachs placement papers PDF download, Goldman Sachs previous year questions with solutions, Goldman Sachs coding questions, and Goldman Sachs interview questions. All papers are completely free and require no registration.
We provide Goldman Sachs placement papers from recent years including 2024 and 2025. Our collection is regularly updated with the latest questions and exam patterns.
Goldman Sachs placement process includes: 1. Online Assessment (90 minutes) - Coding questions and mathematical aptitude, 2. Technical Interview Round 1 (45 minutes) - Data structures and algorithms, 3. Technical Interview Round 2 (45 minutes) - System design and technical deep dive, 4. Managerial Round (45 minutes) - Behavioral and technical discussion, 5. HR Interview (30 minutes) - General discussion and role expectations. Total duration: 3-4 weeks from application to offer.
Goldman Sachs online assessment is 90 minutes long with 2-3 medium to hard coding problems covering arrays, strings, dynamic programming, and graphs. It also includes mathematical aptitude questions on probability, statistics, and quantitative reasoning. The assessment is conducted on platforms like HackerRank.
Goldman Sachs interview process consists of 5 rounds: 1. Online Assessment (90 minutes), 2. Technical Interview Round 1 (45 minutes), 3. Technical Interview Round 2 (45 minutes), 4. Managerial Round (45 minutes), 5. HR Interview (30 minutes). Total duration: 3-4 weeks from application to offer letter.
Goldman Sachs technical interview questions include: Coding Problems (arrays, strings, dynamic programming, graphs), System Design (trading platforms, low-latency systems, risk management systems), Data Structures (trees, graphs, hash maps, optimization), Technical Concepts (OOPs, databases, networking basics), and Project Discussion (technologies used, challenges, scalability). All questions focus on problem-solving ability and technical depth.
Goldman Sachs eligibility criteria for freshers 2025: Minimum 70% or 7.0+ CGPA across 10th, 12th, and graduation. Degree required: B.Tech/B.E./M.Tech in Computer Science, IT, or related fields. Final year students or recent graduates (within 2 years) are eligible. No active backlogs. Strong programming skills in Java, Python, or C++ preferred.
Goldman Sachs eligibility criteria for freshers 2026 are the same as 2025: Minimum 70% or 7.0+ CGPA across all academic levels, B.Tech/B.E./M.Tech in CS/IT or related fields, final year students or recent graduates, no active backlogs, and strong programming fundamentals.
The minimum CGPA required for Goldman Sachs is 7.0 CGPA (70%) across 10th, 12th, and graduation. However, candidates with higher CGPA (8.0+ or 80%+) have better chances of selection. The CGPA requirement is consistent across all roles for freshers.
Goldman Sachs typically allows and expects proficiency in C, C++, Java, and Python for coding sections. Java and Python are most commonly used in their technology divisions. Candidates should be comfortable with at least one of these languages and understand object-oriented programming concepts.
Goldman Sachs salary for freshers (2025): Analyst: ₹18-22 LPA for new graduates, Associate: ₹25-30 LPA (1-2 years experience), Vice President: ₹40-50 LPA (3-5 years). All figures are total annual compensation including base salary, bonuses, and benefits. Salaries may vary based on location (Mumbai, Bangalore) and role.
Goldman Sachs offers Analyst roles for freshers in technology divisions. These roles focus on software development, system design, risk management systems, and trading platforms. Opportunities exist in Mumbai and Bangalore offices.
To prepare for Goldman Sachs placement: 1. Data Structures & Algorithms (40% time) - Focus on arrays, trees, graphs, dynamic programming, 2. Coding Practice (30%) - Solve medium to hard problems on LeetCode, HackerRank, 3. System Design (15%) - Trading systems, low-latency systems, distributed systems, 4. Technical Interview Prep (10%) - Core CS subjects, projects discussion, 5. Aptitude & Math (5%) - Quantitative reasoning, probability, statistics. Focus on strong problem-solving skills.
Focus on: Data Structures (arrays, trees, graphs, hash maps), Algorithms (dynamic programming, greedy algorithms, graph algorithms), System Design (low-latency systems, distributed systems, trading platforms), Programming (Java, Python, C++), and Mathematics (probability, statistics, quantitative reasoning). See the preparation strategy section for detailed topic breakdown.
Preparation time varies: Intensive 3-month plan for candidates with strong DSA background, Extended 6-month plan for comprehensive preparation from basics. Focus on consistent practice, solving 200+ coding problems, and understanding system design fundamentals.
Goldman Sachs offers: High compensation packages with performance bonuses, exposure to cutting-edge financial technology, opportunities to work on low-latency trading systems, strong learning and development programs, global brand recognition, and career growth opportunities. The company values innovation, technical excellence, and impact-driven work.
Goldman Sachs work culture is fast-paced, high-performance, and results-driven. The company values technical excellence, innovation, and collaboration. Teams work on challenging problems in financial technology, trading systems, and risk management. Work-life balance initiatives and wellness programs are available.
Goldman Sachs: Strong technology focus, high compensation (₹18-22 LPA for freshers), emphasis on system design and low-latency systems, global brand recognition.
JP Morgan: Large technology division, competitive salaries (₹16-20 LPA for freshers), focus on banking technology and digital transformation.
Morgan Stanley: Strong technology teams, competitive packages (₹17-21 LPA for freshers), emphasis on financial technology and innovation.
Choose Goldman Sachs if you want strong focus on system design and low-latency systems. Choose JP Morgan/Morgan Stanley if you prefer larger technology divisions or different technology focus areas.
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Ready to start your Goldman Sachs preparation? Practice with our placement papers and focus on strong fundamentals in data structures, algorithms, and system design. Master coding problems and prepare for technical interviews to maximize your chances of success.
Pro Tip: Focus on system design for financial systems and low-latency applications. Goldman Sachs values candidates who can design scalable, high-performance systems for trading and risk management.
Last updated: November 2025