Freelance Data Scientists in Faridabad
Freelance Data Scientists in Faridabad
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Ajay Bidyarthy
Delhi, India
AI Solutions, Software Architect, AI Agents, Fractional CTO
15
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AI Solutions, Software Architect, AI Agents, Fractional CTO
2
I specialize in transforming complex datasets into intuitive, visually compelling dashboards that drive strategic decision-making. With deep expertise in BI tools and data analytics, I design interactive, real-time reporting systems that help businesses uncover trends, monitor KPIs, and optimize performance. My approach combines data storytelling, clean UI/UX, and scalable architecture to deliver impactful insights. đš My Project Portfolio: đ 1. Executive Business Intelligence Dashboard Built a dynamic KPI dashboard for C-level executives Integrated multiple data sources (CRM, ERP, marketing platforms) Delivered real-time insights on revenue, growth, and performance Tools: Power BI, SQL, Azure đ 2. E-commerce Analytics Dashboard Designed a dashboard tracking sales, customer behavior, and conversion rates Implemented cohort analysis and funnel visualization Improved marketing ROI tracking by 40% Tools: Tableau, Python, Google Analytics đ 3. Financial Performance & Forecasting Dashboard Developed financial models and forecasting dashboards Visualized cash flow, P&L, and budget vs actuals Enabled data-driven financial planning Tools: Power BI, Excel, DAX đ 4. Operations & Supply Chain Dashboard Created logistics tracking and inventory monitoring system Real-time alerts for stock levels and delays Reduced operational inefficiencies Tools: Looker Studio, BigQuery đ 5. AI-Powered Analytics Dashboard Integrated machine learning predictions into dashboards Automated anomaly detection and trend analysis Delivered predictive insights for decision-making Tools: Python, TensorFlow, Streamlit
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Iâve worked on building graph database solutions to handle complex, highly connected data that traditional relational databases struggle with. The main goal was to model relationships more intuitively and enable faster, more meaningful queriesâespecially for use cases like recommendations, fraud detection, and network analysis. Tech Stack âGraph Databases: Neo4j âQuery Language: Cypher âBackend: Python (FastAPI / Flask) âData Processing: Pandas âVisualization: Neo4j Bloom / D3.js âCloud & Deployment: AWS / Docker
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Businesses today generate a lot of data, but most of it goes unused. Teams often rely on manual analysis or basic tools that canât uncover deeper patterns. This leads to missed opportunitiesâwhether itâs predicting customer behavior, detecting anomalies, or automating repetitive tasks. Another challenge is that even when machine learning models are built, they are rarely integrated into real workflows. So instead of driving impact, they stay as isolated experiments.
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I design and manage database systems using Elasticsearch, Neo4j, and Supabase to enable high-speed search, rich data relationships, and scalable backend architectures. My work includes building efficient data models, optimizing performance, and ensuring secure, reliable access. I oversee the full lifecycleâfrom setup and integration to deployment and continuous optimization.
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192
Data Scientist
(7)
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Chhavi Verma
Delhi, India
Data Science and Visualization Expert
1x
Hired
5.0
Rating
10
Followers
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Data Science and Visualization Expert
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Books Data Analysis
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Books Data Analysis
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Red Wine Analysis
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Hi Contra community! Just wrapped a rewarding project for Nauvyashreeâdelivered deep-dive EDA, custom visualizations, and rich survey sentiment analysis across four datasets. Each milestone included well-designed PDFs packed with clear charts and approachable explanationsâmaking insights accessible for all audiences. I went the extra mile with collaborative Google Meet sessions to walk the client through every analysis, helping connect the findings to big-picture goals. Feedback was fantastic, and milestone-based payments made the process smooth and transparent. This project really strengthened my ability to turn complex results into stories that empower client decision-making. If you want visually engaging, client-focused analyticsâor need easy-to-follow reports and hands-on walkthroughs for your next projectâletâs connect!
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93
Data Scientist
(3)
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Pratik Bhambri
Dadri, India
Data Scientist: Python, RStudio, ML, BI, NLP, DL, LLM
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Data Scientist: Python, RStudio, ML, BI, NLP, DL, LLM
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Portfolio Optimization Project
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4
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Stock Prediction from Time Series
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Customer Segmentation Project
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4
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"AI-Powered Fraud Detection System | 99.96% AUC"
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5
Data Scientist
(4)
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Himanshu Narwal
Delhi, India
Transforming complexity into clarity through data.
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Transforming complexity into clarity through data.
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Use data science Python libraries to forecast housing prices
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12
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Develop a responsive Python dashboard
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15
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Compare machine learning classification algorithms
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Winning space race with data science
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26
Data Scientist
(4)
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Victory Joseph
Delhi, India
Data Science with Machine Learning Algorithms Expertise
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Data Science with Machine Learning Algorithms Expertise
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Project on Anomaly Detection using Graph Neural Networks
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Project on Logistics in the aspect of Supply Chain Operations
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A project on Game Theory based on Mathematical Models
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15
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Project on Multi-Objective Decision Analysis - TOPSIS
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15
Data Scientist
(12)
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Shrisha
Ghaziabad, India
Aspiring dev crafting practical, reliable systems.
New to Contra
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Aspiring dev crafting practical, reliable systems.
2
Deepfake Detection System Problem: Deepfake accessibility creates real risksâmisinformation, identity fraud, digital trust erosion. I built a production-grade detector: fast, accurate, explainable, CPU-deployable. Approach: Transfer learning with ResNet-50 (25.5M params, pre-trained ImageNet-1K V2). Rather than training from scratch on limited data, I leveraged rich hierarchical features that transfer exceptionally well to detecting artifact patterns (blending boundaries, color mismatches, compression artifacts). Key Decisions: Face-Centric Preprocessing: OpenCV DNN crops faces to 224Ă224, concentrating attention on artifact-rich regions (eyes, mouth, jawlines). Custom Classification Head: Bottleneck design (2048â512â1) with Focal Loss, label smoothing, progressive unfreezingâprevents overfitting on ~4,000 Ciplab images. Explainable AI: Custom Grad-CAM generates attention heatmaps showing exactly where the model detected artifacts. Real-World Robustness: Trained on JPEG compression, Gaussian noise, blur augmentations to handle compressed video feeds. Results: AUC-ROC: 0.9424 | Accuracy: 87.25% | Precision/Recall: 87.27%/84.81% Inference: <100ms per face on CPU Live on Hugging Face Spaces (no GPU) Tech: PyTorch, OpenCV, Albumentations, Gradio. Images, videos, live webcamâone codebase. Demonstrates: End-to-end AI engineering with deliberate trade-offs (efficiency over raw accuracy), training discipline (Focal Loss, Cosine Annealing), and production-first thinking (CPU compatibility, interpretability, real-world robustness). Demo: https://huggingface.co/spaces/Shri04/deepfake-detector
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JobTracker AI â AI-Powered Job Application Tracker
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Government School ERP System â Full-Stack Platform for a Real Government School Client Designed and built a bilingual, full-stack ERP system for a government school in Uttar Pradesh â replacing paper attendance registers, handwritten admission forms, and manual Mid-Day Meal logs with a secure, role-based digital platform. Architected the full data layer â a 25+ model relational schema (PostgreSQL + Prisma) mapped directly from the client's actual government paperwork, including India's UDISE+ admission forms and Form-34 Transfer Certificates, not a generic template. Built defense-in-depth security â role-based access control enforced at the server layer (not just route guards), brute-force account lockout, and a login system designed around a real constraint: students without personal phones authenticate by admission number instead. Shipped a bilingual UI from day one â Hindi and English throughout, using next-intl, so the interface actually works for the people using it, not just the developer testing it. Automated the admission pipeline end-to-end â a 30+ field digital intake form (photo + document uploads to cloud storage) that auto-generates student accounts and credentials in a single atomic transaction. Still actively building â Mid-Day Meal tracking and automated report card generation are next. Open to freelance and contract work where someone needs to own both the system architecture and the day-to-day execution. If it's real, complex, and needs to actually ship â let's talk.
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Full-Stack AI-Powered Job Search Platform | Next.js ¡ TypeScript ¡ PostgreSQL ¡ Groq AI ¡ n8n Built a production-ready web application to help job seekers manage their entire job hunt in one place â replacing messy spreadsheets with an intelligent, automated pipeline. Developed a drag-and-drop Kanban board tracking applications across 6 stages (Applied â Offer â Rejected) with real-time updates Integrated Groq LLaMA 3.3 70B via n8n automation workflows to power an AI chat assistant that lets users query and update their pipeline conversationally Built an ATS Resume Scorer â paste any JD to get a 0â100 match score, keyword gap analysis, strengths/gaps breakdown, and interview likelihood rating Built an AI Resume Tailor with two modes: section-by-section suggestions and a full ATS-optimised rewrite â output downloadable as .txt Implemented Google OAuth auth, serverless PostgreSQL (Neon), PDF resume parsing, and JD auto-extraction â all at $0/month infrastructure cost Stack: Next.js 16 ¡ TypeScript ¡ Prisma ¡ PostgreSQL (Neon) ¡ Groq API ¡ n8n ¡ NextAuth.js ¡ Docker
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Data Scientist
(1)
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Vikas Kashyap
Delhi, India
Data visualization engineer, Data Analyst, BI Expert
11
Followers
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Data visualization engineer, Data Analyst, BI Expert
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Power BI Dashboard for Paris Olympics 2024
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Executive Summary Dashboard for Google Merchandise Store
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National Accident Statistics Dashboard in Google Looker Studio: I built an interactive Looker Studio dashboard using Google Sheets as the data source to visualize national accident statistics. The report analyzes accidents by region, time, severity, and demographics. A scheduled data re:fresh every 15 minutes keeps the dashboard updated in real time. As a Data Visualization Expert, I combined automation and design to deliver a clean, insightful, and dynamic Looker Studio dashboard for data-driven decision-making. đ đŻ đ
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Ecommerce Analytics Dashboard in Looker Studio
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5
Data Scientist
(1)
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Ankit Jha
Gurugram, India
Driving Innovation with AI, Data & Strategy â¨
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Driving Innovation with AI, Data & Strategy â¨
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AI-Driven Fintech Product Launch for UK bank : A case study
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25
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KPI Strategy Overhaul: A Case Study in Strategic Alignment
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Ushering in a new era of AI-powered healthcare abundance
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