Siddharth Nishtala

Data Scientist

https://talent.gravityer.com/siddharth-nishtala

Senior Data Scientist at Accertify.

Accertify

Key Strengths

Demonstrated interest in Data Science and Machine Learning through multiple personal projects (DQN-Trader, Music-Mood-Classifier, SSCCNN, cost-sensitive-trees-rl, People-Supply-Chain, cs6910_assignment3).
Proficiency in Python, a core language for Data Science.
Experience with deep learning (DQN, CNN, Seq2Seq models) and reinforcement learning.
Practical application of data science concepts in competitive settings (Capgemini's Tech Challenge).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards personal learning and exploration in data science and machine learning, which aligns with a culture of continuous improvement and innovation. However, the projects are exclusively personal, and there's only one current professional experience listed, which is also as a Data Scientist. This indicates a focused interest but lacks diversity in team-based or cross-functional project experience, which might impact cultural fit in highly collaborative environments. The 'experienceLevel' is 0, which contradicts the 'Data Scientist' role at Accertify, suggesting a potential data discrepancy or very early career stage.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

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Projects

cost-sensitive-trees-rl

November 6, 2023 – January 9, 2024

Learn decision tree policies in reinforcement learning.

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SSCCNN

December 11, 2021 – August 17, 2023

This repository has the source codes of the Single-Shot Corrective CNN

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Epidemic-Calculator

July 8, 2021 – September 6, 2021

Epidemic-Calculator — GitHub repository

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cs6910_assignment3

April 19, 2021 – May 25, 2021

Training Seq2Seq models with and without attention for a machine transliteration task

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siddharthnishtala.github.io

March 14, 2021 – Present

siddharthnishtala.github.io — GitHub repository

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CS6741

February 21, 2021 – May 9, 2021

CS6741 — GitHub repository

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DQN-Trader

October 31, 2018 – October 31, 2018

Trading using Deep Q Learning

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People-Supply-Chain

October 31, 2018 – March 5, 2020

My solution for the round 2 and 3 of the data science challenge of Capgemini's Tech Challenge 2018.

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Music-Mood-Classifier

December 17, 2017 – December 17, 2017

Breaks a song into frames, extracts relevant features and predicts the mood of each frame individually.

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CSD207-Project-RogueCrawler

November 9, 2016 – December 8, 2016

Group Name: Group members: Harsh Manral, Swagat Kumar, Siddharth Nishtala, Kranthi Kumar Madhavaram, Pratyaksh Tandon

View Project

Key Strengths

Demonstrated interest in Data Science and Machine Learning through multiple personal projects (DQN-Trader, Music-Mood-Classifier, SSCCNN, cost-sensitive-trees-rl, People-Supply-Chain, cs6910_assignment3).
Proficiency in Python, a core language for Data Science.
Experience with deep learning (DQN, CNN, Seq2Seq models) and reinforcement learning.
Practical application of data science concepts in competitive settings (Capgemini's Tech Challenge).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

Siddharth Nishtala

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit