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REQUIREMENT_ID_1628 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Ardem
Type
Opportunity Type Internship
Salary
Stipend / Salary {'@type': 'QuantitativeValue', 'value': '', 'unitText': 'YEAR'}
Location
Location Remote
Posted Date
Posted Date Oct 07, 2026
Excel
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Aptitude Practice Questions & Mock Tests Open Resource β†—
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
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Company-Specific Interview Preparation Corner Open Resource β†—
Detailed interview experiences, exam formats, and previous test questions for Ardem and tech roles.
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Technical Placement Cheat Sheets & Question Bank Open Resource β†—
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
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Algorithm, DSA & Live Code Debugger Practice Open Resource β†—
Hands-on problem sets to improve coding speed and step-by-step memory debugging.

The ideal candidate should have strong attention to detail, good communication skills, sound knowledge of MS Excel, and the ability to work independently while maintaining accuracy, productivity, and quality standards.

About the Role ARDEM Data Services is looking for a detail-oriented and analytical Data Analyst – BOL Processing to support client operations by accurately processing and validating Bills of Lading (BOL) data in the client system. The role involves reviewing source documents, extracting relevant information, entering data accurately into the client system, validating records, identifying discrepancies, and coordinating with internal teams for clarification and resolution. Key Responsibilities BOL Data Processing Process Bills of Lading (BOL) accurately in the client-provided system. Review BOL documents and identify relevant data fields required for processing. Extract, enter, and update information accurately in the designated system. Ensure all required fields are completed correctly before submitting records. Follow defined process guidelines, work instructions, and client-specific requirements. Maintain consistency and accuracy while processing high volumes of documents. Data Validation & Quality Verify entered information against source documents before final submission. Identify missing, incorrect, inconsistent, or duplicate information. Perform data validation and necessary corrections within the defined process. Maintain high levels of accuracy while meeting daily productivity targets. Escalate exceptions, unclear information, and process-related issues to the appropriate team. Follow quality control procedures and incorporate feedback to improve accuracy. CRM / System Management Use Salesforce or similar CRM/business systems for data entry, tracking, and record management. Update records accurately and maintain data integrity within the system. Navigate multiple system screens and applications efficiently. Follow system-specific procedures for creating, updating, and reviewing records. Maintain proper documentation of exceptions and pending items. Coordination & Communication Coordinate with internal teams for clarification, updates, and issue resolution. Communicate process-related concerns clearly and professionally. Escalate critical or unresolved issues within the defined turnaround time. Respond to internal queries related to assigned work. Maintain effective communication with team members and supervisors. Productivity & Process Compliance Manage multiple tasks and priorities effectively. Complete assigned work within defined turnaround times. Consistently meet productivity, quality, and accuracy expectations. Follow company policies, process SOPs, security guidelines, and client requirements. Maintain confidentiality and appropriate handling of client information. Adapt to process changes, new instructions, and system updates. Reporting & Documentation Maintain accurate records of completed and pending work. Provide required status updates to the reporting manager/team. Track exceptions, errors, and pending cases as required. Support the team in preparing operational reports and maintaining process documentation.

Ardem 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 🎯
Ardem Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Ardem 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 (Excel) & 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
Ardem 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 Ardem as a Data Analyst?
Preparation Tip: Highlight Ardem's market reputation, recent tech innovations, and how your skills in Excel 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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