Artificial Intelligence, Machine Learning & Data
Government or privateData Scientist
Entry track: Skills + portfolio + hiring assessments · Entrance/qualification path + employer/institute recruitment
Where are you right now?
Typical time from here: 8–20 months
How you get in
JEE/engineering entrances, CUET, GATE CS/DA/EC/EE, JAM/statistics routes, postgraduate admissions, internships, coding/data assessments and research recruitment
Exam pages on StudyBddy
What you must have
B.Tech/B.E., B.Sc./M.Sc. in CS, mathematics, statistics or related fields; MCA/M.Tech/PhD for specialised research roles
The gate that decides it
Strong portfolio
First evidence to build
End-to-end tabular ML
Your first 90 days
Days 1–30: eligibility and diagnostic in Python; linear algebra. Days 31–60: core practice in Supervised/unsupervised learning; deep learning. Days 61–90: complete End-to-end tabular ML and obtain one external review.
Realistic first roles
- ML intern
- junior data scientist
- AI engineer
Core tools and platforms
The 9-phase route for this post
Data Scientist follows the Machine Learning, AI & Data Science Engineering route.
Phase 0 · Target, Eligibility & Reality Check
Map transferable work evidence, salary/time constraints and exit risk. Reserve a sustainable weekly schedule, choose a low-risk pilot project and verify whether Strong portfolio; relevant degree preferred; GATE/PG route for advanced research roles; cloud/ML credentials optional is mandatory or only advantageous.
Typical duration: 1–2 weeks
Phase 1 · Foundation & Academic Base
Use a part-time bridge plan: 45–90 minutes on weekdays plus one weekend practical block. Prioritise gaps that block entry rather than relearning the entire degree.
Typical duration: 6–16 weeks
Phase 2 · Core Curriculum / Skill Stack
Leverage domain experience, but complete the target role’s non-negotiable core. Use workplace-safe sample problems and avoid misrepresenting confidential work.
Typical duration: 3–9 months
Phase 3 · Applied Practice, Projects & Field Exposure
Create bridge evidence that uses transferable strengths while demonstrating target skills. Use personal/public data or approved internal projects; protect confidentiality.
Typical duration: 2–6 months
Phase 4 · Exam, Credential, Licence or Advanced Qualification
Choose credentials only when they unlock the target role. Schedule exam preparation around work cycles and verify age, attempts, experience and licence rules.
Typical duration: 3–18 months, route-dependent
Phase 5 · Experience, Network & Professional Evidence
Build internal cross-functional experience, contribute to communities or open projects and develop references without neglecting current-job performance.
Typical duration: 2–6 months, may overlap
Phase 6 · Portfolio, CV, Applications & Selection Preparation
Frame the transition positively, quantify transferable achievements and address seniority or salary reset honestly. Prepare target-role cases and references.
Typical duration: 4–12 weeks
Phase 7 · Selection, Joining & First 90 Days
Respect domain norms, seek explicit expectations and avoid overusing previous-role authority. Deliver quick wins without skipping foundational learning.
Typical duration: First 90 days
Phase 8 · Growth, Specialisation & Position-to-Position Progression
Use promotions, lateral moves, postgraduate study, domain credentials, publications, leadership or independent practice only when tied to the next role.
Typical duration: 1–5 years per progression step
Other posts on the same route
Check it at the source
- https://gate.iitk.ac.in/
- https://scikit-learn.org/stable/user_guide
- https://docs.pytorch.org/tutorials/
- https://www.kaggle.com/
These roles normally require separate private, campus, research-lab, or government recruitment after education and skill development. Verify current eligibility, dates and recruitment rules from the official notification.