Role Overview
We are looking for a versatile Data Scientist who can build robust data pipelines — from web scraping to AI/ML deployment. The ideal candidate is comfortable working across the full data and AI lifecycle: extracting data at scale, transforming and storing it reliably, and using it to train, deploy, and maintain machine learning models in production.

Key Responsibilities
Design, build, and maintain scalable web scraping scripts/pipelines using Python (e.g., BeautifulSoup, Scrapy, Selenium, Playwright)
Handle dynamic websites, pagination, anti-bot mechanisms, proxies, and rate-limiting strategies
Clean, transform, and normalize scraped data (structured/unstructured) before storage
Design MongoDB schemas and collections optimized for the type of data being handled
Implement logic to identify and update unique/duplicate records efficiently (upserts, deduplication strategies)
Schedule and monitor data pipelines/jobs (via cron, Airflow, or similar orchestration tools)
Ensure data quality, consistency, and integrity across pipelines, including error logging, retries,



and failure recovery
Support end-to-end AI/ML lifecycle: data collection, preprocessing, feature engineering, model selection, training, and validation
Fine-tune machine learning/deep learning models and evaluate performance against business requirements
Package and deploy models into production environments (APIs, batch pipelines, etc.)
Implement and maintain MLOps practices — versioning (models & data), CI/CD for ML, monitoring model performance/drift
Collaborate with cross-functional teams to integrate AI models with existing data pipelines, including scraped/transformed data as model input

Required Skills

Core:
Solid proficiency in Python (writing clean, modular, production-grade code)
Hands-on experience with MongoDB (schema design, aggregation pipelines, indexing, upsert/dedup logic)
Web scraping tools/libraries: BeautifulSoup, Scrapy, Selenium, Playwright, or similar
Data transformatio

📌 Data Scientist (India)
🏢 VCBay
📍 India