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REQUIREMENT_ID_110 β€’ 3-DAY_ACTIVE_POLICY

Trade Operations Analyst

Company
Company zanskar
Type
Opportunity Type Internship
Salary
Stipend / Salary 4-6 LPA
Location
Location Bangalore
Posted Date
Posted Date Yesterday
Python SQL Linux Excel attention to detail tradeOps data entry basic financial concepts
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Aptitude Practice Questions Open Resource β†—
Helps you sharpen quantitative and logical reasoning skills required for the online test at Zanskar.
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Company Interview Preparation Guide Open Resource β†—
Provides insights into typical interview formats and sample questions for fintech roles like Trade Operations Analyst.
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Interview Preparation Resources Open Resource β†—
Offers curated interview experiences and tips that can help you navigate Zanskar's selection process.
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Coding Practice Problems Open Resource β†—
Contains a variety of SQL and Python coding challenges to boost your problem‑solving ability for the technical round.

Bachelor's degree in Computer Science, Commerce, Mathematics, or related field; Minimum 60% aggregate; No active backlogs; Fresh graduates of 2025‑2027 batches are welcome; Strong analytical mindset and willingness to learn.

1
Round 1: Online aptitude test
2
Round 2: Technical interview (SQL & Python basics, problem‑solving)
3
Round 3: HR interview (fit & motivation)
Zanskar is an emerging fintech platform focused on building robust trading infrastructure for institutional and retail investors. Headquartered in Bangalore, the company combines cutting‑edge technology with deep market expertise to deliver low‑latency trade execution, real‑time risk monitoring, and seamless post‑trade services. With a culture that encourages rapid learning, cross‑functional collaboration, and ownership, Zanskar has quickly become a preferred workplace for young technologists who want to make an impact in the financial services domain. The Trade Operations Analyst role is an entry‑level position designed for fresh graduates or early‑career professionals who are eager to dive into the world of trade processing and operations support. Reporting to senior trade engineers, the analyst will assist in daily trade reconciliation, monitor system dashboards, and help maintain the integrity of trade data. This role offers a structured learning path, allowing the candidate to acquire hands‑on experience with trading lifecycles, incident handling, and basic data analysis while being mentored by seasoned professionals. Key Responsibilities: 1. Perform manual trade entry and reconciliation checks against system records. 2. Execute routine data verification and maintain accurate trade logs. 3. Monitor trading system dashboards, flagging anomalies for senior engineers. 4. Run pre‑written SQL queries to extract trade‑related data for reporting. 5. Create and update simple spreadsheets and trackers to document daily activities. 6. Assist senior engineers by gathering information for incident tickets and status updates. 7. Document standard operating procedures, checklists, and incident notes. 8. Support the team in basic incident triage and escalation following defined protocols. 9. Participate in regular knowledge‑sharing sessions to build understanding of order lifecycle, execution flow, and fills. 10. Continuously improve process efficiency by suggesting automation opportunities under guidance. Tech Stack & Tools: Linux/Unix environment, Python (basic scripting), SQL, Excel, internal trade monitoring dashboards, ticketing systems. Growth Path: Over the first 6‑12 months, the analyst will transition from manual processing to handling more complex data validation tasks, eventually contributing to automation scripts and minor system enhancements. Successful performers can progress to Trade Operations Engineer, Senior Analyst, or move into specialized roles such as Trade Surveillance or Product Support. Why Join Zanskar? The company offers a vibrant learning ecosystem, exposure to real‑time trading environments, and mentorship from industry veterans. Fresh talent gets the chance to work on mission‑critical systems, develop a strong foundation in financial technology, and grow within a fast‑scaling organization that values innovation and employee development.

zanskar β€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
zanskar Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for zanskar and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
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 (Python, SQL, Linux, Excel, attention to detail, tradeOps, data entry, basic financial concepts) & 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
zanskar Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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.
Why do you want to join zanskar as a Trade Operations Analyst?
Preparation Tip: Highlight zanskar's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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