Aakaash M S

Data Scientist

https://talent.gravityer.com/aakaash-m-s

Software Engineer Intern at Thermo Fisher Scientific

Thermo Fisher Scientific

Key Strengths

Demonstrated experience with various machine learning models including LSTM and transformer-based NLP (DistilBERT).
Experience in cloud deployment for ML models (AWS SageMaker, DynamoDB, Azure Power BI Embedded).
Proficiency in Python and Jupyter Notebook for data science projects.
Exposure to advanced topics like Multi-Agent Reinforcement Learning (MARL) and RAG with local LLMs.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards data science and machine learning, aligning well with a Data Scientist role. The diversity of projects (finance, healthcare, NLP, smart grids) indicates a broad interest and adaptability. However, the experience level is listed as 0, and the current role start date is in the future, which suggests a very junior or aspiring profile. This discrepancy impacts the cultural fit for a senior role.

Soft Skills & Operational Fit

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

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

ai-resume-analyzer

May 28, 2026 – Present

An AI-powered resume analyzer that uses RAG and local LLMs to evaluate resumes.

View Project

marl-smartgrid-pricing

September 16, 2025 – Present

A Multi-Agent Reinforcement Learning (MARL) based pricing and incentive strategy for demand response in smart grids.

View Project

MultiCloud-Stock-Forecasting-Analytics

March 24, 2025 – March 24, 2025

Developed a MultiCloud Stock Forecasting system using LSTM, deployed on AWS SageMaker for training, AWS DynamoDB for storage, and Azure Power BI Embedded for analytics.

View Project

Multivariate-Stock-Price-Forecasting

February 26, 2025 – April 3, 2025

Multivariate-Stock-Price-Forecasting — GitHub repository

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fake-news-detection-distilbert

February 16, 2025 – April 22, 2025

This project aims to detect fake news using DistilBERT, a transformer-based NLP model.

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Fake-News-Detection

February 9, 2025 – February 10, 2025

Fake-News-Detection — GitHub repository

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Lung-Cancer-Detection

January 30, 2025 – February 9, 2025

Lung-Cancer-Detection — GitHub repository

View Project

MPI

January 26, 2025 – February 13, 2025

MPI — GitHub repository

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Haskell

January 24, 2025 – April 16, 2025

Haskell programs focusing on fundamental concepts such as recursion, pattern matching, and higher-order functions.

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Personal-Health-Fitness-D2

January 6, 2025 – June 6, 2025

Software Engineering Cross Platform App

View Project

Key Strengths

Demonstrated experience with various machine learning models including LSTM and transformer-based NLP (DistilBERT).
Experience in cloud deployment for ML models (AWS SageMaker, DynamoDB, Azure Power BI Embedded).
Proficiency in Python and Jupyter Notebook for data science projects.
Exposure to advanced topics like Multi-Agent Reinforcement Learning (MARL) and RAG with local LLMs.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

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

Aakaash M S

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit