Omkar Pawar
Computer VisionAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer | NLP, Deep Learning, IoT Integration | Built SmartDoc AI & Predictive Systems | Python, Flask, Streamlit | From Data to Deployment (End-to-End ML)
Turning data into decisions and AI into real-world impact. I’m a Data & AI professional with 2.5+ years of experience building end-to-end machine learning systems and data-driven solutions. I work at the intersection of analytics, ML, and product thinking—using Python, NLP, and visualization tools to solve real business problems and create scalable AI applications. In my current role, I’ve engineered automation pipelines processing 100K+ records, reducing manual reporting time by 70%. I’ve built real-time Power BI dashboards, deployed production-grade ML models, and worked on predictive maintenance and AI-driven systems. From credit risk modeling (85%+ accuracy) to intelligent document analysis and NLP-based applications, I focus on solutions that are not just accurate—but actually usable in production. Right now, I’m looking to grow into roles where I can build impactful AI/ML solutions at scale—whether that’s as a Data Scientist, ML Engineer, or AI-focused Analyst. I’m especially interested in solving complex business problems, working with strong teams, and contributing to products that make a measurable difference.
Uttaranchal University
BCA(computer application), Computer Programming, Specific Applications
January 1, 2025 – February 1, 2028
ITI mulund
Electronic mechanic
August 1, 2021 – July 1, 2023
Techpaathshala
Data science
N/A – Present
Skylink Communication
Product designer / Analyst
October 1, 2023 – Present
Bhandup · On-site
Vinayak Electricals - India
Electronic Specialist
September 1, 2022 – October 1, 2022
Mumbai, Maharashtra, India · On-site
Skyline delta ai support
March 1, 2026 – Present
Skylink Delta AI Intercom Support — customers can ask questions about their intercom system in plain language and get instant answers. 🔧 Tech Stack: → Python (backend server) → SQLite (database) → HTML/CSS/JS (frontend) → AI knowledge base from official manual → Deployed on Render 🌐 Live: skylink-delta-ai-model.onrender.com 💻 GitHub: github.com/omkar87796-sudo/SKYLINK-DELTA-AI-MODEL #Python #AI #WebDevelopment #FullStack #OpenSource
SmartDoc AI — Full Stack AI Platform
January 1, 2026 – Present
Built a production-ready full-stack AI platform that demonstrates end-to-end data science and AI engineering skills in a single deployable application. The platform allows users to upload any file (CSV, Excel, PDF, image) and instantly run: • Real ML models — Random Forest, SVM, Logistic Regression, Decision Tree, Gradient Boosting, KMeans clustering • Deep Learning inference — ANN, CNN, LSTM, GRU, Encoder-Decoder, Transformer architectures • Time-series forecasting — LSTM/GRU with confidence intervals, trend analysis, error metrics • RAG document chat — extract and query real content from uploaded PDFs and CSVs • Power BI ready reports — automatic Excel export with multi-sheet model results Tech: React + Vite (frontend), Python FastAPI (backend), scikit-learn, pandas, NumPy. Deployed on Vercel + Render.
Bank Credit Approval Decision System
January 1, 2026 – January 1, 2026
I built an end-to-end Credit Risk Assessment System using Random Forest to support loan approval decisions and reduce wrong approvals. 🔹 Key Highlights: • Data preprocessing & feature engineering • Automated missing value handling • Random Forest model with high ROC-AUC performance • Enterprise-style Streamlit UI for bulk customer risk evaluation • Complete ML pipeline & deployment on Streamlit Cloud This project simulates real-world banking scenarios and focuses on minimizing risky approvals while improving decision quality. 🔗 GitHub: https://github.com/omkar87796-sudo/Bank-Credit-Approval-Decision-System 🔗 Live App: (https://bank-credit-approval-decision-system-eeruqrmq2prupvcbya3rfw.streamlit.app/) I’m currently exploring Machine Learning, Deep Learning, and Generative AI and open to learning & collaboration opportunities.
Crowdfunding
August 1, 2025 – Present
Skills: power point · Microsoft Power BI
Statistics
Techpaathshala
June 23, 2026 – Present
Machine Learning
Techpaathshala
June 23, 2026 – Present
Deep Learning
Techpaathshala
June 23, 2026 – Present
Python
Techpaathshala
June 23, 2026 – Present
SQL
Techpaathshala
June 23, 2026 – Present
Power BI
Techpaathshala
June 23, 2026 – Present
Advanced Excel
Techpaathshala
June 23, 2026 – Present
Gen AI
Techpaathshala
June 23, 2026 – Present
Data Science
Techpaathshala
June 23, 2026 – Present
Gen AI & AI Tools
Techpaathshala
June 23, 2026 – Present
personal branding
Techpaathshala
June 23, 2026 – Present
soft skill
Techpaathshala
June 23, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards AI/ML and full-stack development, which aligns with a technically driven culture. The open-source contributions and deployment of live applications demonstrate initiative and a desire to share work. However, the target role is 'Computer Vision', and while there's deep learning experience (CNNs), specific computer vision projects or detailed experience are not explicitly highlighted, which might indicate a gap in direct cultural fit for a specialized CV role. The breadth of skills across data science, web development, and AI suggests adaptability.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions and collaborate with cross-functional teams, suggesting a proactive and problem-solving approach. The 'personal branding' and 'soft skill' certifications, while not detailed, imply an awareness of professional development. However, without direct assessment data, a definitive evaluation of soft skills and operational fit is limited.