Gowlapalli Rohit

Data Scientist

https://www.opentalent.in/gowlapalli-rohit

Hyderabad, IndiaMember since June 13, 2026

Key Strengths

Demonstrated experience in Python for data-related tasks (Semantic Textual Similarity, SMAI-A2, ELMo, Static-Word-Embeddings).
Exposure to machine learning concepts and implementations (PCA, Hierarchical Clustering, GMM, N-gram, CNN, RNN, LSTM, BERT, MiniLM).
Familiarity with Jupyter Notebook for data analysis and model development.
Experience with distributed systems (Distributed-Shared-Memory) which can be beneficial for large-scale data processing.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards academic and personal technical exploration, particularly in machine learning and data science. The diversity of projects, from blockchain to distributed systems, indicates a broad technical curiosity. However, the lack of professional experience or team-based projects makes it difficult to assess cultural fit in a collaborative work environment. The target role 'Data Scientist' aligns well with several of the candidate's personal projects.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical implementation.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

Semantic-Textual-Similarity

June 21, 2025 – June 21, 2025

Developed a Semantic Textual Similarity model, achieving a Pearson correlation of 0.89 on test data, outperforming traditional statistical and standalone neural network approaches. Implemented and evaluated N-gram based methods, CNN, RNN, LSTM, BERT, and a knowledge distillation approach using MiniLM.

View Project

Distributed-Shared-Memory

March 28, 2025 – May 19, 2025

Implemented a fault-tolerant distributed key-value store in Go using master-slave replication, automatic failover, quorum-based writes, and majority-vote reads. Included client resilience, write-ahead logging, and a command-line interface for scaled testing across multiple nodes.

View Project

ELMo-Deep-Contextualized-Word-Representations

March 20, 2025 – March 28, 2025

ELMo-Deep-Contextualized-Word-Representations — GitHub repository

View Project

Static-Word-Embeddings

February 15, 2025 – March 28, 2025

Static-Word-Embeddings — GitHub repository

View Project

SMAI-A2

September 7, 2023 – September 27, 2023

Contains Implementation of various methods like PCA , HIerarchial Clustering , Bayesian Information Criterion and Guassian MIxture Model

View Project

Air-Quality-Monitoring-System

June 7, 2023 – June 14, 2023

Developed a MERN stack based dashboard that displayed graphs of air pollution data from an OM2M enabled node with various sensors.

View Project

Airdrop-Insurance

June 7, 2023 – June 9, 2023

The Airdrop Insurance project is a decentralized application (DApp) that uses the Flutter framework for the user interface and the Firebase platform for backend services. The DApp allows users to purchase insurance policies using their mobile devices. The policies are stored on the Ethereum blockchain using smart contracts written in Solidity.

View Project

Science-II

January 31, 2023 – April 26, 2024

Contains Course-work I have done as part of Science-II course curriculum

View Project

Pig_Game-Simulator

December 29, 2022 – July 7, 2023

Virtual Dice Game built using Javascript

View Project

IIITH_CSE_SEM-3_Resources

December 4, 2022 – October 16, 2023

Contains Resources related to Courses like Automata Theory , Data & Applications , Embedded Systems Workshop , Operating Systems and Networks , Probability & Statistics , Real-Analysis , Algorithm Analysis and Design

View Project

Key Strengths

Demonstrated experience in Python for data-related tasks (Semantic Textual Similarity, SMAI-A2, ELMo, Static-Word-Embeddings).
Exposure to machine learning concepts and implementations (PCA, Hierarchical Clustering, GMM, N-gram, CNN, RNN, LSTM, BERT, MiniLM).
Familiarity with Jupyter Notebook for data analysis and model development.
Experience with distributed systems (Distributed-Shared-Memory) which can be beneficial for large-scale data processing.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical implementation.

Gowlapalli Rohit

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit