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REQUIREMENT_ID_261 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company TRISM
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 5 LPA
Location
Location Hyderabad
Posted Date
Posted Date Today
SQL Python Excel Tableau PowerBI Data cleaning Data visualization Statistical analysis Business communication Problem solving
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Aptitude Practice Questions Open Resource β†—
Helps you sharpen quantitative and logical reasoning skills required for the online screening test.
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Company Interview Preparation Guide Open Resource β†—
Provides generic interview strategies and common questions that can be adapted for TRISM's selection process.
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TRISM Data Analyst Interview Guide Open Resource β†—
Specific insights, sample questions and tips collected from previous candidates applying for Data Analyst roles at TRISM.
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Algorithm and Data Structure Problem Set Open Resource β†—
Strengthens coding fundamentals and problem‑solving ability, useful for technical rounds focusing on Python and SQL logic.

Graduates with B.E/B.Tech in Computer Science, Information Technology, Electronics, or B.Sc in Statistics, Mathematics, Economics. Minimum 60% aggregate (or CGPA 6.0/10). Must belong to the 2022‑2026 batch. No active backlogs at the time of joining. Strong analytical mindset and good communication skills are essential.

1
Round 1: Online aptitude test
2
Round 2: Technical interview (SQL/Python & case study)
3
Round 3: HR interview
TRISM is an emerging analytics and technology solutions provider headquartered in Bengaluru, India. Founded in 2018, the company has quickly built a reputation for delivering data‑driven insights to clients across retail, finance, healthcare and e‑commerce sectors. With a workforce of over 300 professionals, TRISM blends cutting‑edge tools with domain expertise to help businesses make smarter decisions. The firm emphasizes a collaborative culture, continuous learning, and a strong focus on innovation, making it an attractive destination for fresh talent looking to grow in the data space. As a Data Analyst at TRISM, you will be at the heart of the decision‑making engine. You will work closely with product managers, engineers, and business stakeholders to transform raw data into actionable intelligence. The role offers exposure to end‑to‑end analytics workflows – from data ingestion and cleaning to visualization and storytelling. You will get hands‑on experience with industry‑standard tools and will be mentored by senior analysts who have years of experience in large‑scale data projects. Key Responsibilities: 1. Analyze and interpret large business datasets to uncover trends, patterns and insights. 2. Create interactive dashboards, reports and visualizations using Tableau, PowerBI or similar tools. 3. Clean, validate, and maintain data quality across multiple sources. 4. Collaborate with cross‑functional teams to understand data requirements and deliver solutions. 5. Translate analytical findings into clear, actionable recommendations for business leaders. 6. Develop and maintain SQL queries, stored procedures and data pipelines. 7. Perform ad‑hoc analysis to support product launches, marketing campaigns and operational improvements. 8. Document analytical processes, data dictionaries and reporting standards. 9. Stay updated with emerging analytics techniques and suggest process enhancements. 10. Participate in knowledge‑sharing sessions and contribute to the team’s best‑practice repository. Tech Stack: SQL, Python (pandas, numpy), Excel, Tableau, PowerBI, Git, and basic knowledge of cloud data warehouses (Snowflake/BigQuery). Familiarity with statistical concepts and data modeling is a plus. Growth Path: Starting as a Junior Data Analyst, high performers can progress to Senior Analyst, then to Lead Analyst or Analytics Manager within 2‑4 years, with opportunities to specialize in data engineering or data science. Why Join TRISM: The company offers a fast‑paced environment where you can see the impact of your work on real business outcomes. You will receive mentorship, regular training, and exposure to a diverse portfolio of clients, accelerating your professional development in the analytics domain.

TRISM 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 🎯
TRISM Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for TRISM 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 (SQL, Python, Excel, Tableau, PowerBI, Data cleaning, Data visualization, Statistical analysis, Business communication, Problem solving) & 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
TRISM 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 TRISM as a Data Analyst?
Preparation Tip: Highlight TRISM's market reputation, recent tech innovations, and how your skills in SQL 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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