Akhilesh Singh

Data Scientist

https://talent.gravityer.com/akhilesh-singh

Turning data into intelligence — Computer Vision, NLP & LLMs | Python | AI/ML Intern @ ZenithraTech

New Delhi, Delhi, India

Key Strengths

Strong foundational knowledge in Python for data science and machine learning.
Extensive practical experience with various ML algorithms (SVM, Logistic Regression, KNN, YOLOv8) demonstrated through personal projects.
Proficiency in using Jupyter Notebook for data analysis and model development.
Experience with real-time applications like face recognition and pedestrian tracking.
Exposure to AI-powered applications using Google's Gemini API.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate demonstrates a strong interest in machine learning and data science through numerous personal projects. The diversity of projects, ranging from intent classification to fraud detection and real-time tracking, indicates a proactive and curious mindset. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative environment.

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

sales-analytics-system

January 14, 2026 – Present

sales-analytics-system — GitHub repository

View Project

meeting-summarizer

January 2, 2026 – Present

meeting-summarizer — GitHub repository

View Project

ErAkhileshSingh

November 11, 2025 – Present

ErAkhileshSingh — GitHub repository

View Project

pedestrian-tracking

November 3, 2025 – November 21, 2025

Custom-trained YOLOv8-based pedestrian detection and tracking system using Python and OpenCV. Includes dataset creation, model training, and benchmarking pipeline for real-time performance evaluation.

View Project

FaceRecognition

November 1, 2025 – November 11, 2025

Real-time face recognition and attendance system using Python, OpenCV, and face_recognition library. Detects, identifies, and logs attendance with automatic image encoding and storage.

View Project

My-Intent-App

October 3, 2025 – November 21, 2025

🤖 An AI-powered intent classifier built with Python, Google's Gemini API, and Streamlit. It analyzes user queries to determine intent and suggest actions.

View Project

svm-classification-project

September 4, 2025 – Present

An SVM model in Python to classify data using linear and RBF kernels.

View Project

Logistic_Regression_BreastCancer

August 29, 2025 – August 29, 2025

Logistic Regression project on Breast Cancer dataset using sklearn

View Project

KNN-Iris-Classifier

August 29, 2025 – November 21, 2025

KNN Classifier on Iris dataset using Python.

View Project

fraud-detection-app

July 4, 2025 – October 4, 2025

A machine learning-powered application designed to detect fraudulent activities in transactional data. This project enables users to analyze, flag, and report potentially suspicious transactions using state-of-the-art algorithms, robust data processing, and interactive dashboards. Features include customizable detection

View Project

Key Strengths

Strong foundational knowledge in Python for data science and machine learning.
Extensive practical experience with various ML algorithms (SVM, Logistic Regression, KNN, YOLOv8) demonstrated through personal projects.
Proficiency in using Jupyter Notebook for data analysis and model development.
Experience with real-time applications like face recognition and pedestrian tracking.
Exposure to AI-powered applications using Google's Gemini API.

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.

Akhilesh Singh

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit