Joel Alex

Data Scientist

https://talent.gravityer.com/joel-alex

Learner | Coder | Problem Solver

Bengaluru, Karnataka, IndiaMember since June 19, 2026

Key Strengths

Demonstrated interest and practical experience in various Data Science sub-fields including LLMs, image processing, and stock prediction.
Proficiency in Python and Jupyter Notebook, essential tools for Data Scientists.
Experience with deep learning models (LSTM, FNN, MobileNetV2, ESPCN) and frameworks (NVIDIA NeMo).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and demonstrate a strong inclination towards individual exploration and development. While this shows initiative, there is no information regarding collaborative projects or team-based work, which are crucial for cultural fit in many organizations. The project diversity aligns well with a Data Scientist role, but the lack of professional experience or team projects limits the assessment of cultural fit.

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

Aikya-Billing-Agent

June 3, 2026 – Present

Aikya-Billing-Agent — GitHub repository

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stock-data-pipeline

December 7, 2025 – December 7, 2025

stock-data-pipeline — GitHub repository

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web-research-streamlit

September 3, 2025 – September 3, 2025

A web-research agent based on gemini model along with Streamlit interface.

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Persona-Generator-Reddit

July 14, 2025 – July 14, 2025

An LLM based Persona Generator based on a user's latest comments

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heuristic-solver

May 30, 2025 – November 25, 2025

heuristic-solver — GitHub repository

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llm-based-mcq-generator

May 26, 2025 – May 30, 2025

It's an llm based mcq generator

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asr-nemo-nvidia

May 25, 2025 – May 25, 2025

Used NVIDIA STT conformer model to be production ready with FastAPI and Docker

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semantic-segmentation-on-Oxford-IIIT-dataset

August 17, 2024 – August 24, 2024

Used Oxford IIIT dataset containing 37 classes with 200 images for each to train a custom image segmentation model

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Image-Pixelation-Detection-And-Correction

July 15, 2024 – August 23, 2024

This repository offers a comprehensive solution for detecting and removing image pixelation using deep learning models. It leverages MobileNetV2 for pixelation detection and ESPCN for high-quality depixelation.

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NIG_LSTM-Model

May 6, 2024 – December 6, 2024

These are the set of codes that I have implemented when studying the results of fourier transform and market sentiment in prediction of stock prices. I have also included a model which uses concepts of brownian motion to predict stock prices using an FNN and also Normal Inverse Gaussian with an LSTM.

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Key Strengths

Demonstrated interest and practical experience in various Data Science sub-fields including LLMs, image processing, and stock prediction.
Proficiency in Python and Jupyter Notebook, essential tools for Data Scientists.
Experience with deep learning models (LSTM, FNN, MobileNetV2, ESPCN) and frameworks (NVIDIA NeMo).

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.

Joel Alex

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit