Devesh

ML Engineer

https://talent.gravityer.com/devesh-2

ML Engineer

Fractal Analystics

Key Strengths

Demonstrated interest in Machine Learning through various personal projects.
Experience with diverse ML models (Ensemble Learning, Time Series, Sentiment Analysis, Churn Prediction).
Exposure to data pipeline concepts using PySpark and Hive.
Familiarity with Jupyter Notebook for data science workflows.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong focus on individual technical exploration in ML. While this indicates self-driven learning, there is no explicit evidence of team collaboration or diverse project types beyond ML/data science, which limits the assessment of broader cultural fit. The single professional experience entry is current and in an ML Engineer role, aligning with the target 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

LLMOps

February 4, 2026 – Present

LLMOps — GitHub repository

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Ensemble_Learning-on-a-Bank-Dataset

November 10, 2020 – November 10, 2020

Ensemble_Learning-on-a-Bank-Dataset — GitHub repository

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Time_Sereis_Problem-Forecasting-Passengers

November 10, 2020 – November 10, 2020

Time_Sereis_Problem-Forecasting-Passengers — GitHub repository

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TensorFlow-Implementations

November 3, 2020 – November 3, 2020

Pytorch and TensorFlow Implementations

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Sentiment-Analysis-using-Keras

November 3, 2020 – November 3, 2020

Sentiment Analysis using Doc2vec.

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Create-A-Data-Pipeline-Based-On-Messaging-Using-PySpark-And-Hive---Covid-19-Analysis--Project

November 3, 2020 – November 12, 2020

Create-A-Data-Pipeline-Based-On-Messaging-Using-PySpark-And-Hive---Covid-19-Analysis--Project — GitHub repository

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retailPriceOptimization

October 31, 2020 – October 31, 2020

Retail Price optimization Probleam

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EDA_examples

September 12, 2020 – November 3, 2020

This Repo will has EDA explained examples, Some of them are in "Python" and some are in "R".

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customerChurn

September 12, 2020 – September 12, 2020

This repo has all ML Models applied on Customer Churn Dataset to identify churn.

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Java-JSP-Online-Departmental-Store

March 22, 2018 – March 22, 2018

JSP based Online Departmental Store Management Portal

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Key Strengths

Demonstrated interest in Machine Learning through various personal projects.
Experience with diverse ML models (Ensemble Learning, Time Series, Sentiment Analysis, Churn Prediction).
Exposure to data pipeline concepts using PySpark and Hive.
Familiarity with Jupyter Notebook for data science workflows.

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.

Devesh

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit