◉ Start with the simplest models
◉ Identify the patterns from data
◉ Let the data speak
◉ Don't force data to cry
◉ Spend most of your time in EDA, preprocessing and feature engineering
◉ Choose the tech stack with which you are more familiar
◉ Try to involve people with domain expertise.
◉ Visualize your data. It helps a lot in understanding the patterns.
◉ Use statistical inference to understand the underlying distributions
◉ Initially solve what is possible
◉ Do market research
◉ See what other data scientists are doing in the same domain
◉ Try to relate the results of your work with the business value
◉ Communicate your findings
❓ Want to add anything?
Feel free to share your thoughts in the comments below!