AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Key Strengths

Strong foundational skills in Python for data science and machine learning, evidenced by multiple projects.
Experience with various machine learning models (Random Forest) and data visualization (interactive maps).
Demonstrated ability to build end-to-end data-driven applications, including prediction and visualization components.
Exposure to AI/ML in security contexts (NIDS, SOC, SIEM agents) indicates a broad interest in applying data science.
Proficiency in using Jupyter Notebook for data analysis and model development.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate has a strong portfolio of personal projects, demonstrating initiative and a passion for technology. The projects span data science, machine learning, and cybersecurity, indicating a diverse interest and willingness to explore different domains. However, the projects are predominantly personal, and there is no information on collaborative work or experience in a professional team setting, which limits the assessment of cultural fit in a corporate environment. The target role is 'Data Scientist', and many projects align well with this, particularly those involving predictive modeling and data analysis.

Soft Skills & Operational Fit

The candidate's project descriptions are clear and concise, indicating good communication skills in a technical context. The focus on personal projects suggests self-motivation and a proactive approach to learning and development. However, without psychometric test results or interview data, it's difficult to assess other soft skills like teamwork, stress handling, or logical reasoning.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Atharva Amle

Data Scientist

https://www.opentalent.in/atharva-amle

MumbaiMember since June 14, 2026

https://www.opentalent.in/atharva-amle

Top Skills

Jupyter NotebookPythonJavaScriptHTMLCSSShell

Skills

Jupyter NotebookPythonJavaScriptHTMLCSSShell

Projects

securevault

May 12, 2026 – Present

Secure file sharing system featuring zero-knowledge AES-256-GCM encryption, Argon2id password hashing, TOTP multi-factor authentication, VirusTotal malware scanning, expiring share links, and a live audit dashboard with brute-force detection.

View Project

File-Type-Identifier

May 8, 2026 – Present

A CLI-based file type identification tool using magic number signatures — with entropy analysis, hash generation, VirusTotal lookup, polyglot detection, and JSON/CSV reporting.

View Project

multi-agent-soc

May 5, 2026 – Present

Autonomous multi-agent SOC powered by CrewAI + local LLM. Detects, investigates & triages security incidents using 4 AI agents — triage, threat hunting, forensics, and reporting — with MITRE ATT&CK mapping, AbuseIPDB/VirusTotal enrichment, and a Streamlit HITL analyst dashboard.

View Project

agent-siem

May 4, 2026 – Present

Autonomous SIEM platform — ReAct LLM agent investigates alerts, queries a ChromaDB vector store, enriches IOCs via VirusTotal + AbuseIPDB, and auto-blocks threats via Windows Firewall. Streamlit SOC dashboard with geo map + AI analyst chat.

View Project

soar-incident-response-platform

May 3, 2026 – Present

Automated SOAR platform: ML-based detection → VirusTotal enrichment → auto-response

View Project

network-intrusion-detection-system

May 1, 2026 – Present

ML + AI based NIDS with real-time Scapy detection and Streamlit SOC dashboard

View Project

Athar2410

April 26, 2026 – Present

Athar2410 — GitHub repository

View Project

disaster-relief-prediction

February 9, 2026 – Present

machine learning model to predict the amount of supplies needed based on the statistics of the disaster

View Project

arduino-simulator

February 3, 2026 – Present

This is a simulation platform to play around with an arduino-uno, LED and a push button

View Project

Water-Borne-Disease-predictor-with-Location-Hotspot-Visualization

August 2, 2025 – Present

Predict water-borne disease risk from individual or batch data using a Random Forest model. Visualize high-risk locations on an interactive map.

View Project

Key Strengths

Strong foundational skills in Python for data science and machine learning, evidenced by multiple projects.
Experience with various machine learning models (Random Forest) and data visualization (interactive maps).
Demonstrated ability to build end-to-end data-driven applications, including prediction and visualization components.
Exposure to AI/ML in security contexts (NIDS, SOC, SIEM agents) indicates a broad interest in applying data science.
Proficiency in using Jupyter Notebook for data analysis and model development.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit