An initiative by the Academy for Competitive Data ScienceThe Career Assistant
A Claude project set up with a resume and instructions.
For professionals with under 3 years' experience
Learned data science. Still working in another field?
Python, SQL, ML, maybe a certification or executive programme. What's missing is a way to test your background against real Data/AI openings and act on it.
See the complete career-switch system built live.
Live online · 3 hours · [DATE] · [TIME] IST · Laptop recommended
A 3-hour live workshop. We build a Career Assistant in Claude and run it on real openings, starting from a real work background. You see every step, then set up your own on the free Claude plan.
An initiative by the Academy for Competitive Data Science
Your switch, as one loop
- Profile
- Assistant
- Jobs
- Fit
- Apply
- Prep
- Track
- Next step
↻ Repeats for every new opening
You're not a fresher. So why does the switch still feel like guesswork?
- Which Data/AI role do I actually fit?
- Does my 2 years of experience count, or am I starting over?
- Applied to 30 jobs. Why haven't I heard back?
- Should I do another certification first?
- Why does every application feel like a fresh guess?
- I keep asking AI if I'm ready. Why does the answer keep changing?
The problem may not be your skills or your experience. It may be that nothing connects them.
60-second career switch check
Is it the roles you're targeting? Your experience? Your resume?
Where is your career switch getting stuck?
Answer 5 quick questions and see which part of your switch to focus on first.
Built on the 5 parts every career switch goes through · Anonymous, nothing stored
You already know the tools.
They just don't work together.
- ChatGPT
- Claude
- Course certificates
- Resume tools
- Job portals
- Interview questions
- Skill-gap notes
- Application tracker
One career context
↓One repeatable process
Where the workshop starts
Before you apply, understand what the market is actually asking for.
Your industry already has AI problems worth solving. We start with which roles exist, what each level asks for, and how your domain can be your edge.
AI/ML role types
- Data Scientist
- ML Engineer
- NLP Engineer
- Computer Vision Engineer
- GenAI / LLM Engineer
- MLOps Engineer
- Applied Scientist
Role levels
- 1. Associate / Entry
- 2. Junior
- 3. Mid-level
- 4. Senior
Most switchers enter at Associate or Junior level. Your domain experience helps you move up faster.
E.g. Pune, Chennai
Mechanical / Manufacturing
Knows: machines, downtime, defects, quality control
ML Engineer (predictive maintenance) · Computer Vision Engineer (defect detection)
E.g. Mumbai
Finance / Banking
Knows: credit, transactions, risk, compliance
Data Scientist (credit risk, fraud) · GenAI Engineer (document intelligence)
E.g. Bengaluru, Hyderabad
QA / Support / Tech Ops
Knows: tickets, logs, test data, customer issues
NLP Engineer (ticket classification) · MLOps Engineer
E.g. Gurugram, Noida
Operations / Supply Chain
Knows: demand, inventory, routes, delivery timelines
Data Scientist (forecasting) · ML Engineer (demand prediction)
E.g. Mumbai, Delhi
Sales / Marketing / Business Ops
Knows: customers, campaigns, pipelines, churn
Data Scientist (churn, recommendations) · AI Product roles
The same skill, different fit
Python + ML can fit a Data Scientist role in your industry well, and an ML Engineer role expecting production deployment poorly.
Representative examples, not guaranteed paths. Your own directions come from testing your background against real postings.
Your domain isn't a detour. It can be the dataset you understand better than anyone.
The system we build
One job in. A complete decision system out.
Your background goes in once, with your work experience translated into honest evidence, never passed off as Data Science. Every posting then runs through the same 8 steps.
Illustrative example · sample data
Example profile
Banking operations analyst, Mumbai · 2 years
Executive PG programme in Data Science · Python · SQL · ML projects
Target: Risk / Credit Analytics, Data Analyst
You submit applications yourself. No auto-apply, no mass applying, no scraping.
One posting. One connected process.
Repeatable every time.
What the system produces
3 hours. One live session.
The complete system, shown step by step.
We build the full Career Assistant live in Claude and run it on a real posting. You see every step, then set up your own on the free Claude plan.
Master resume
Generated from a real background. Nothing invented.
Two skill files
career-assistant · linkedin-optimizer, and how they're installed.
Ranked shortlist
Real openings sorted Strong / Possible / Weak.
Tailored resume
For one real posting, gaps stated honestly.
Scored mock interview
5–7 role-specific questions with a readiness rating.
Application tracker
Every application, status and next step in one place.
LinkedIn drafts
Headline, About and experience drafts, plus a recruiter-search check. You review and paste.
The workshop shows you a repeatable system to plan, navigate, and pursue your career move.
The live workshop · 3 hours
Four blocks. One complete system, built live.
- Block 1≈25 min
The market
How Data/AI hiring works for career switchers, and why this workshop is taught this way.
- Block 2≈60 min
The Career Assistant, built live
We set up the Career Assistant live, then run it end to end on real openings for a target role.
- Block 3≈15 min
Bonus: LinkedIn optimiser
Draft your headline, About and experience from the same resume.
- Block 4Remaining time
Live Q&A
Your questions and your own situation.
What you'll need
To attend: a phone or laptop (laptop recommended). To set up your own afterwards: a laptop, your resume (or a paragraph about your work) and a free Claude account. No coding needed.
Note: All timings are approximate.
WHO'S TEACHING
V VIJAY
Lead Instructor · Tech Co-founder
Cofounder, CareerAssist AI
Vijay holds a B.S. in Data Science and Applications from IIT Madras, where he graduated with a CGPA of 9.7+ and received the Academic Distinction Award. An avid programmer, he actively develops AI-powered solutions, combining strong academic foundations with hands-on experience in building real-world applications.
Animesh Tiwari
AI & Data Capability Advisor · Educator
Founder, Academy for Competitive Data Science
Animesh is an ex-Dell, Master Black Belt from the Indian Statistical Institute, and a consistently top-rated instructor on leading ed-tech platforms including Great Learning and upGrad. He has held leadership positions across banking, telecom, and technology, bringing a strong blend of industry, data, and business experience.
Good fit
This is for you if…
- ✓You're working, with under 3 years' experience, in a role outside core Data/AI.
- ✓You've learned Data Science, ML or AI through college, certifications or an executive programme, and built projects.
- ✓You're unsure which role fits you, or whether your experience counts.
- ✓You want a focused, practical session, not another long course.
Not a fit
Probably not for you if…
- ✕You already work in Data/AI and want career advancement.
- ✕You're a fresher looking for your first job.
- ✕You're just starting to learn Data/AI. This assumes you've already learned it.
- ✕You want a guaranteed job.
- ✕You want an inflated resume that hides gaps.
Questions, answered.
Live online workshop · 3 hours
₹299
One-time payment
Built live. Learn how to set up your own.
- Date
- [DATE]
- Time
- [TIME] IST
- Format
- Live online
One-time payment · Secure checkout via Razorpay · Non-refundable
Your next move shouldn't be another guess.
You've learned the skills and built real work experience. Now connect them to the roles you want.
From
“I've learned Data Science, but I keep guessing where I fit.”
To
“I know which roles I'm targeting, how my experience counts, and what I'm doing next.”
[DATE] · [TIME] IST · Live online · Laptop recommended