Priyansh Agrawal

Data Scientist

https://www.opentalent.in/priyansh-agrawal-1

IndiaMember since June 16, 2026

Key Strengths

Strong foundational understanding of Natural Language Processing (NLP) demonstrated by the 'Spelling-and-Grammatical-Error-Correction' project using N-gram models, HMM, and Naive Bayes.
Experience with machine learning algorithms, specifically SVM (Pegasos implementation).
Proficiency in Python, a core language for Data Science.
Exposure to data structures and algorithms through LeetCode practice and linear hashing implementation.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic in nature, focusing on core algorithm implementations and theoretical concepts. While demonstrating technical curiosity, there is insufficient data to assess collaboration, adaptability, or alignment with a typical corporate data science team culture. The project diversity is good, but the direct alignment with industry-standard data science workflows (e.g., MLOps, cloud platforms, large-scale data processing) is not evident.

Soft Skills & Operational Fit

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

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Projects

CRUD_app

July 16, 2022 – March 15, 2023

CRUD_app — GitHub repository

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AKE_exp

November 19, 2021 – November 19, 2021

AKE_exp — GitHub repository

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code

September 2, 2021 – August 26, 2022

Collection of LeetCode questions to ace the coding interview! - Created using [LeetHub](https://github.com/QasimWani/LeetHub).

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Secure-FTP

July 13, 2021 – July 30, 2021

Designed and built a basic TCP oriented Secure File Transfer Protocol (SFTP) with Diffie-Hellmann key exchange protocol, modified Caesar Cipher for encryption, DSS signature scheme and SHA1 for password hashing.

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Pegasos

May 5, 2019 – June 29, 2021

Modified SVM algorithm called Pegasos implemented with Python

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Automatic-Keyword-Extraction-Data

March 26, 2019 – March 26, 2019

Repository containing different published datasets (original and processed format) used for Automatic Keywords Extraction (AKE).

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Spelling-and-Grammatical-Error-Correction

December 27, 2018 – July 4, 2021

Built a system from scratch in Python which can detect spelling and grammatical errors in a word and sentence respectively using N-gram based Smoothed-Language Model, Levenshtein Distance, Hidden Markov Model and Naive Bayes Classifier.

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Digital-Signature

August 11, 2018 – August 11, 2018

Implementation of a digital signature scheme

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linear_hashing

August 7, 2018 – August 7, 2018

Implementation of linear hashing algorithm to handle duplicate elimination using c++ language. Ref. paper ->

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SQL-Engine

August 6, 2018 – July 4, 2021

A Minified SQL Engine is written in Python that can run a subset of DML queries given by the user.

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Key Strengths

Strong foundational understanding of Natural Language Processing (NLP) demonstrated by the 'Spelling-and-Grammatical-Error-Correction' project using N-gram models, HMM, and Naive Bayes.
Experience with machine learning algorithms, specifically SVM (Pegasos implementation).
Proficiency in Python, a core language for Data Science.
Exposure to data structures and algorithms through LeetCode practice and linear hashing implementation.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

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

Priyansh Agrawal

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit