🗓️ Table 1: Registration Details
| Category | Information |
|---|---|
| Registration Period | 12th September – 3rd October |
| Mode | Online Registration |
| Next Step | Assessment details shared with eligible candidates after registration closes |
| Eligibility | Final-year or recent graduates (as per Virtusa criteria) |
⚙️ Table 2: Selection Rounds
| Round | Name | Mode | Description |
|---|---|---|---|
| Round 1 | Technical Assessment + SpeechX | Online | Covers technical fundamentals and communication skills |
| Round 2 | Coding Assessment | Online | Hands-on coding round to test logic and problem-solving |
| Round 3 | Technical + Communication Interview | In-person (Virtusa Office) | Face-to-face technical + communication evaluation |
| Round 4 | HR Discussion | In-person / Online | Final HR fitment, salary, and project discussion |
💻 Table 3: Technical & Coding Skills
| Category | Key Topics |
|---|---|
| Programming | Core Java, Pseudocode (Basics & Recursion) |
| Database | SQL / MySQL (Basics, Joins, Subqueries) |
| Concepts | Data Structures, OOPS Concepts, Operating System Basics |
| Coding | Problem Solving, Power Coding, DSA Practice |
🗣️ Table 4: Aptitude & Communication Skills
| Skill Type | Focus Areas |
|---|---|
| Analytical Ability | Logical Reasoning, Problem Solving |
| Numerical Ability | Quantitative Aptitude, Basic Maths |
| Verbal Ability | Grammar, Vocabulary, Reading Comprehension |
| Communication | SpeechX Round – Pronunciation, Fluency, Writing Skills |
Tips to Prepare an ATS-Friendly Resume :-
Getting your resume noticed by the Applicant Tracking System is super important if you want employers to actually see it. I’ll give some tips to help make your resume look good to the computer system if you’re applying to be a Data Scientist.
1. Keep it simple. Don’t use crazy fonts, tables, or anything too wild. Stick to basics like clear section headings (“Skills,” “Experience”).
2. Load up on keywords. Pull words right from the job description – Python, Machine Learning, whatever. Show you have the technical and people skills they want.
3. Use normal job titles. “Data Scientist” or “Analyst,” not “Future CEO.”
4. Put key info in the body text. No footers! Recruiters might not see em. Keep your name, address, LinkedIn front and center.
5. Save as a .docx or .pdf file. Make sure the pdf isn’t an image or anything weird. Give it a professional name too like “FirstName_LastName_Resume”.
6. Show you got the right background. Internships, projects, anything to prove you can handle a Data Science job. Numbers help – “improved model by 15%” tells em you get results.
7. Use bullet points, not paragraphs. Easier to scan.
8. Show off certifications and schoolin’. DataCamp, Coursera courses, a math/CS degree – make em shine! 9. Nix the images and logos. Recruiters tech can’t handle em.
10. List technical skills first. Python, R, SQL – they wanna see you have these specifically.
11. Check for typos! Sloppy resumes might get tossed by the robot gatekeepers.
12. Test it out first. Free online tools can scan your resume before you submit to catch issues.
Follow this advice and you’ll be all set to pass the ATS recruiters and get that interview!
Tips for acing the job interview:-
Do’s:
– Look into the company and the stuff they need help with.
– If you don’t get something, ask them to explain More.
– Walk them through how you think about fixing problems.
– Use real examples from past work to show your skills.
– Stay calm and confident. Work through problems slowly, even if you aren’t sure.
Don’ts:
– Don’t guess if you aren’t sure. Explain your thinking.
– Keep your answers simple and clear.
– Remember to talk about teamwork, communication, and problem fixing.
– Take your time to think before answering.
– Ask good questions to show you care about the job and team.
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