PLACED AT SCRY ANALYTICS

From Ambition to Data Scientist

Manjeet Pathak turned his ambition into achievement with Uncodemy's Data Science program. Through focused training in Python, machine learning, statistics, and analytics, he secured a 4.8 LPA offer as a Data Scientist at Scry Analytics, Noida.

Manjeet Pathak - Student Success

Manjeet Pathak

Data Scientist

Batch
(DA/WD/R-JAN-23) — Uncodemy
Location
Noida
Batch Start Date
Jan 14, 2026 (Career-Focused Track)

4.8 LPA

Salary Package

55

Days to Hire

Scry Analytics

Data Science & AI Firm

Top 6%

Cohort Ranking

The Pivot

Aspiring Analyst Non-Tech Background
CAREER-FOCUSED DATA SCIENCE TRACK
Data Scientist Scry Analytics, Noida

Before the Program

  • No formal training in programming or analytics tools.
  • Uncertain about the right entry path into data science.
  • Weak foundation in statistics, Python, and SQL.
  • No hands-on projects or GitHub portfolio.

After the Program

  • Fluent in Python, SQL, Pandas, and Scikit-learn workflows.
  • Built multiple end-to-end ML projects with clean documentation.
  • Cleared every interview round with structured, confident answers.
  • Landed a full-time Data Scientist role at Scry Analytics.

The Learning Journey Timeline

Phase 1: Building the Base

Started with Python syntax, control flow, and core statistics. Practiced data cleaning and exploratory analysis using Pandas and NumPy on real datasets.

Phase 2: Applied Machine Learning

Moved into regression, classification, and clustering algorithms. Learned model evaluation, feature engineering, and hyperparameter tuning through guided projects.

Phase 3: Interview Readiness

Focused on SQL query practice, case-study discussions, resume refinement, and live mock interviews to build confidence for real hiring rounds.

Core Tech Stack Mastered

Python Pandas & NumPy Machine Learning SQL Tableau & Power BI

Capstone Project Mastery

Loan Default Risk Prediction

Loan Default Risk Prediction

MACHINE LEARNING

A supervised classification project built to predict whether a loan applicant is likely to default, helping financial institutions make smarter lending decisions.

The Challenge:

Working with an imbalanced financial dataset containing missing values, outliers, and mixed feature types that made accurate prediction challenging.

The Solution:

Performed comprehensive EDA, engineered risk-related features, trained Logistic Regression, Random Forest, and XGBoost models, and evaluated them using ROC-AUC, precision, and recall. Delivered a Power BI dashboard for business insights.

Scikit-learn XGBoost Power BI

Performance Scorecard

Python & ML Assessments95%
Case Study Mocks4.4/5
Soft Skills4.6/5

Overcoming Challenges

Manjeet's biggest hurdle was bridging the gap between theory and practice. Concepts like bias-variance tradeoff and feature engineering felt abstract until he began building projects hands-on. Regular mentor sessions and daily coding practice helped him convert confusion into clarity, and by the final phase, he was confidently presenting complete ML pipelines to interviewers.

Interview Preparation Intensive

Mock Interviews

Participated in 12+ mock sessions covering Python, SQL, statistics, and ML concepts with detailed feedback after each round.

Resume Workshops

Redesigned his resume around project outcomes and quantifiable results, making it ATS-friendly and recruiter-ready.

Soft Skills Training

Learned to frame answers using the STAR technique and to explain complex ideas in simple, business-friendly language.

Interview & Placement Process

1

Online Assessment

Solved a timed test with Python, SQL, and basic statistics problems within a strict time limit.

2

Technical Round

Answered live coding and concept-based questions on data wrangling, model selection, and evaluation metrics.

3

Case Study

Walked the panel through a complete ML project — from problem framing to model deployment — with clear reasoning.

4

Managerial Round

Discussed teamwork, adaptability, and long-term career goals in an open conversation with the hiring manager.

The Offer

Scry Analytics

Data Scientist

Joining Scry Analytics in Noida as a Data Scientist, working with a leading data science and AI firm to build analytics-driven products and machine learning solutions.

Trajectory: The Ascent

Manjeet's compensation growth from his early roles to his current Data Scientist position at Scry Analytics, showing the steady climb that ended with a 4.8 LPA offer.

From Beginner to Data Scientist

  • 1.2 LPA — Trainee / Intern
  • 1.8 LPA — Junior Data Analyst
  • 2.6 LPA — Analytics Associate
  • 3.6 LPA — Data Analyst
  • 4.8 LPA — Data Scientist at Scry Analytics
Salary Growth Chart

Trainer & Mentor Team

Mr. Irshad Khan - Ex-KPMG, GlobalLogic

Mr. Irshad Khan

Ex-KPMG, GlobalLogic

Connect on LinkedIn
Mr. Syed Najeeb - Ex-Air India, ISAP India

Mr. Syed Najeeb

Ex-Air India, ISAP India

Connect on LinkedIn
Mr. Kunal Arora - Ex-Noidavery, Keventers

Mr. Kunal Arora

Ex-Noidavery, Keventers

Connect on LinkedIn

"Manjeet brought a rare blend of humility and hunger to every session. He asked sharp questions, revisited weak topics without ego, and treated every project like a real client deliverable. Watching him evolve from writing his first Python function to confidently defending a full ML pipeline in interviews has been deeply satisfying for our team."

- Mentor Panel, Uncodemy

"I walked in with doubts and walked out with an offer letter. The structured curriculum, honest mentor feedback, and real project work made all the difference. This program didn't just teach me data science — it gave me a career."

- Manjeet Pathak

THE DREAM ACHIEVED

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