Data Scraping & Analytics Intern

Onelot; Makati; On-site; PHP 167,000 - 279,000; Part time

Job summary

Onelot in Manila is offering a Data Science Intern role to help build the data backbone powering market insights. You will develop and maintain scrapers that collect used car market data at scale and work with engineers to turn raw data into actionable intelligence.

This internship is ideal for someone who loves Python, data engineering, analytics, and large-scale scraping systems, with hands-on experience in datasets, data cleaning, and reporting to internal teams.

Qualifications

• Pursuing or completed a degree in Computer Science, Data Science, Software Engineering, or similar.
• Familiarity with Python and scraping tools such as BeautifulSoup, Scrapy, or Selenium.
• Basic SQL knowledge.
• Experience in data cleaning, processing, and visualization.
• Understanding of APIs and data extraction techniques.
• Strong analytical and problem‑solving skills.
• Able to work independently and deliver tasks on time.

Responsibilities

• Develop, run, and maintain web scrapers used to collect market data
• Monitor scraper performance and ensure timely, reliable data extraction
• Optimize scrapers for speed, efficiency, and large-scale workloads
• Process and analyze scraped datasets to uncover meaningful insights
• Prepare and share reports with internal teams
• Work with engineers and cross‑functional teams to understand data needs and improve data workflows

Skills

Python

Web scraping

SQL basics

Data cleaning

APIs

Analytical thinking

Independent worker

Education

CS/DS/SE degree

Tools

BeautifulSoup

Scrapy

Selenium

Job description

Onelot in Manila is offering a Data Science Intern role to help build the data backbone powering market insights. You will develop and maintain scrapers that collect used car market data at scale and work with engineers to turn raw data into actionable intelligence.

This internship is ideal for someone who loves Python, data engineering, analytics, and large-scale scraping systems, with hands-on experience in datasets, data cleaning, and reporting to internal teams.