Sapna Singh

Data Scientist

Bangalore, India 1+ yrs exp 88 · Excellent

About

Data Science professional with hands-on experience in data analysis, web scraping, and database-driven application development. Proficient in Python, SQL, and MongoDB with practical experience in REST API development, large-scale data extraction pipelines, and building AI-powered analytics systems.

Skills & Expertise (38)

SQL Intermediate

6.6/10

Years Exp

Python Intermediate

6.6/10

Years Exp

FastAPI Intermediate

6.5/10

Years Exp

MongoDb Intermediate

6.5/10

Years Exp

AI Agents Intermediate

6.4/10

Years Exp

RAG Intermediate

6.4/10

Years Exp

Prompt Engineering Intermediate

6.4/10

Years Exp

Azure OpenAI Intermediate

6.4/10

Years Exp

NLP Intermediate

6.4/10

Years Exp

Time Series Forecasting Intermediate

6.4/10

Years Exp

Model Evaluation Intermediate

6.3/10

Years Exp

Azure functions Intermediate

6.3/10

Years Exp

Postman Intermediate

6.3/10

Years Exp

ARM Templates Intermediate

6.3/10

Years Exp

Random Forest Intermediate

6.3/10

Years Exp

SVM Intermediate

6.3/10

Years Exp

ANN Intermediate

6.3/10

Years Exp

Feature Engineering Intermediate

6.3/10

Years Exp

Selenium Intermediate

6.3/10

Years Exp

Git Intermediate

6.3/10

Years Exp

GitHub Intermediate

6.3/10

Years Exp

Tableau Intermediate

6.3/10

Years Exp

Power BI Intermediate

6.3/10

Years Exp

Requests Intermediate

6.3/10

Years Exp

BeautifulSoup Intermediate

6.3/10

Years Exp

Google Sheets API Intermediate

6.3/10

Years Exp

Async Processing Intermediate

6.3/10

Years Exp

WebSockets Intermediate

6.3/10

Years Exp

Django Intermediate

6.3/10

Years Exp

Studio 3T PyCharm Gemini Conversational AI LLM Applications REST APIs Playwright ADLS Gen2 Microsoft Excel

Work Experience

Data Scientist

Flynava Technologies

Jan 2025 - May 2026

Designed and implemented FastAPI-based REST APIs to integrate and aggregate data from 174 global news sources, enabling category-based content delivery and streamlined data retrieval. Developed large-scale Playwright web scraping pipelines to extract airfare data from 15–20 airline websites, enabling real-time competitor fare monitoring and price trend analysis. Built optimized MongoDB aggregation pipelines to query, transform, and analyze large datasets, improving data retrieval efficiency by 40% and supporting analytics workflows. Executed QA automation and data validation workflows using JSON-based comparison of UI-scraped data against backend MongoDB records, improving data accuracy and reducing manual verification efforts by 70%. Automated competitor footnote change detection, reducing pricing analyst response time by 50% and decreasing footnote error rates from 10–15% to 2–3%.