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REQUIREMENT_ID_101 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst Intern

Company
Company Portcast
Type
Opportunity Type Internship
Salary
Stipend / Salary Rs 15,000/month
Location
Location Remote
Posted Date
Posted Date Yesterday
Python SQL Data cleaning Data analysis Excel Tableau Git Problem solving Communication Attention to detail
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Aptitude and Reasoning Practice Open Resource β†—
Helps you sharpen quantitative and logical reasoning skills commonly tested in the first online assessment round.
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Interview Preparation Guide Open Resource β†—
Covers a wide range of technical interview topics, including SQL queries and Python fundamentals useful for the technical round.
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Portcast Data Analyst Interview Insights Open Resource β†—
Specific interview experiences, sample questions and tips shared by candidates who applied for Data Analyst roles at Portcast.
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Algorithm and Data Structure Practice Open Resource β†—
Provides coding problems to improve problem‑solving speed, which is valuable for Python‑based assessments and on‑the‑spot coding tasks.

Final‑year undergraduate or recent graduate (2025‑2027) in Computer Science, Data Science, Statistics, Information Technology, Engineering or related fields; minimum 60% aggregate (or CGPA 6.0/10); no active backlogs; strong analytical mindset; fluent in English (written & verbal).

1
Round 1: Online assessment (aptitude, SQL & Python basics)
2
Round 2: Technical interview (data quality, QA automation, problem solving)
3
Round 3: HR interview (culture fit, motivation, career goals)
Portcast is a venture‑backed logistics technology startup headquartered in Singapore. Founded in 2018, the company builds a real‑time transportation visibility platform that helps shippers, manufacturers and logistics service providers turn raw data into actionable decisions. Backed by leading technology investors, Portcast combines advanced predictive analytics with a deep understanding of global supply chains to reduce costs, improve operational control and make supply chains more predictable. The team is lean, globally distributed and operates in a remote‑first mode, allowing talent from across Asia and Europe to collaborate on high‑impact problems. As a Data Analyst Intern, you will become an integral part of the Data team that powers the core prediction engine. The role is hands‑on and goes beyond routine checklist tasks – you will be expected to investigate data anomalies, build quality assurance pipelines, and support the integration of new carrier and market data sources. You will work closely with senior Data Analysts and Data Scientists, gaining mentorship while contributing to live production systems that customers rely on daily. Key responsibilities include: 1. Inspect ingested and system‑generated data for gaps, anomalies and inconsistencies, and trace issues back to source systems. 2. Develop, maintain and automate QA checks, reporting scripts and dashboards using Python and SQL. 3. Assist Data Analysts with ad‑hoc customer queries, data extractions and dashboard upkeep. 4. Support the onboarding of new data sources, ensuring seamless integration with existing pipelines. 5. Document data flows, scripts, and findings to enable knowledge sharing across the team. 6. Participate in code reviews and contribute to improving data‑pipeline reliability. 7. Collaborate with cross‑functional teams to understand business requirements and translate them into technical solutions. 8. Continuously learn and apply new tools, including AI‑assisted coding, while validating outputs manually. 9. Provide timely updates on data quality issues and propose corrective actions. 10. Contribute ideas to enhance the overall data strategy and product roadmap. The tech stack revolves around Python (pandas, NumPy), SQL (PostgreSQL/BigQuery), version control (Git), and data‑visualisation tools such as Tableau or PowerBI. Exposure to cloud platforms (AWS/GCP) and containerisation (Docker) is a plus. Successful interns often transition to full‑time roles, moving from data quality tasks to more advanced analytics, model validation and product ownership. Joining Portcast offers the chance to work on cutting‑edge predictive logistics, receive mentorship from seasoned data professionals, and be part of a culture that values curiosity, ownership and impact.

Portcast 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 🎯
Portcast Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Portcast 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, Data cleaning, Data analysis, Excel, Tableau, Git, Problem solving, Communication, Attention to detail) & 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
Portcast 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 Portcast as a Data Analyst Intern?
Preparation Tip: Highlight Portcast'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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