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Nitika Satya | Gravity Talent Portal

Nitika Satya

Nitika Satya

Data Scientist

https://talent.gravityer.com/nitika-satya

I am a second year student pursuing MBA from MICA, Ahmedabad. I have previously worked a business technology analyst at Deloitte US India.

Ahmedabad, Gujarat, India

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Member since June 16, 2026

https://talent.gravityer.com/nitika-satya

Top Skills

R

Skills

R

Projects

Hands-On-Exercise-

September 7, 2017 – September 7, 2017

Hands-On-Exercise- — GitHub repository

K-fold---Titanic-Train-

September 7, 2017 – September 7, 2017

K-fold---Titanic-Train- — GitHub repository

Bank-Data---Logistic-Regression-

September 7, 2017 – September 7, 2017

Bank-Data---Logistic-Regression- — GitHub repository

Student-Merge

September 7, 2017 – September 7, 2017

Student-Merge — GitHub repository

Maths-Science

September 7, 2017 – September 7, 2017

Maths-Science — GitHub repository

Class-13--Random-Forest---new

September 7, 2017 – September 7, 2017

Class-13--Random-Forest---new — GitHub repository

Class-13-Random-Forest

September 7, 2017 – September 7, 2017

Class-13-Random-Forest — GitHub repository

Class-11---Logistics

September 7, 2017 – September 7, 2017

Class-11---Logistics — GitHub repository

Class-3---Reading-and-writing-data

September 6, 2017 – September 7, 2017

Class-3---Reading-and-writing-data — GitHub repository

Class-1---R-environment-

September 6, 2017 – September 6, 2017

Class-1---R-environment- — GitHub repository

Key Strengths

Demonstrated interest in data science concepts through personal GitHub projects.
Exposure to various machine learning algorithms (K-fold, Random Forest, Logistic Regression) in personal projects.
Experience with R environment for data analysis.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects indicate an interest in learning and applying data science techniques. However, the lack of detailed project descriptions, team-based projects, or professional experience makes it difficult to fully assess cultural fit or collaboration potential. The projects are primarily academic or exploratory in nature.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or detailed experience descriptions are available.