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venkatasai Varada | Gravity Talent Portal

venkatasai Varada

venkatasai Varada

Data Scientist

https://talent.gravityer.com/venkatasai-varada

Machine Learning Engineer

University of Connecticut

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

hyderabad, Telangana, IndiaMember since June 16, 2026

https://talent.gravityer.com/venkatasai-varada

Top Skills

RJupyter NotebookPL/SQLPython

Skills

RJupyter NotebookPL/SQLPython

Experience

University of Connecticut

Data Scientist

June 16, 2026 – Present

Projects

ML-models-implementation

October 21, 2025 – October 29, 2025

ML-models-implementation — GitHub repository

interconnect-challenge

September 8, 2021 – September 8, 2021

interconnect-challenge — GitHub repository

Classification---XGB-ELI5-feature-importance

July 4, 2021 – July 4, 2021

Classification---XGB-ELI5-feature-importance — GitHub repository

logistic-regression-including-text-features

May 7, 2021 – May 7, 2021

built a logit model containing countvectoriser features and cont and categorical features

Predicting-Poisonous-Mushrooms

December 11, 2016 – December 17, 2016

Predicting-Poisonous-Mushrooms — GitHub repository

Azureml---Publish-web-service-using-R

October 19, 2016 – October 19, 2016

Azureml---Publish-web-service-using-R — GitHub repository

Visualizing-traffic-violations-in-Maryland

October 19, 2016 – December 18, 2016

Visualizing the number of traffic violations in the state of Maryland over the years 2013-2016 to understand trend

Zappos-Website-customer-data-analysis

September 8, 2016 – September 8, 2016

Zappos-Website-customer-data-analysis — GitHub repository

Business-Process-Modelling-and-Data-Management

July 26, 2016 – March 20, 2017

Business-Process-Modelling-and-Data-Management — GitHub repository

Sentiment-Analysis-in-R

July 6, 2016 – May 2, 2018

Sentiment-Analysis-in-R — GitHub repository

Key Strengths

Demonstrated interest in Data Science through multiple personal projects.
Experience with R and Python for data analysis and machine learning tasks.
Exposure to various machine learning models and data visualization techniques.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards data science and machine learning, which aligns with a Data Scientist role. The diversity of projects, from predictive modeling to sentiment analysis and traffic visualization, indicates a broad interest in applying data science techniques. However, the lack of professional experience beyond a current role at a university (with no start date provided) and the absence of team-based projects make it difficult to fully assess cultural fit and collaboration potential.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.