Have you ever wondered what are the differences between data scientists, data enginers, and data analysts? Ever wanted to know what problems these professionals are hired to solve for companies?

I worked with a San Diego based startup to answer these questions.

Over 26,000 data science job descriptions were scraped and analyzed in to identify common skills sought by companies, skills unique to data scientists vs data engineers vs data analysts, and tasks and problems these professionals solve across various industries.

The byproduct of the project was machine learning models that can identify and extract technical skills and problem phrases from a job description.

A detailed writeup of the analysis process can be found on the GravityAI website.

Technologies Used: Python, Selenium, BeautifulSoup, Scrapy, Spacy, NLTK, Keras