Turo Data Scientist interview questions

Two datasets provided: vehicles - table of all vehicles and their attributes: • technology: 0 if none, 1 if yes (technology that is installed in vehicles that makes them "instantly bookable" and unlockable with mobile phone) • actual_price: actual daily price for vehicle (owners are able to set whatever price they want) • recommended_price: appropriate "market" price for the vehicle, based on our analysis • num_images: number of photos of the car • street_parking: 0 no, 1 yes • description: number of characters of the car description inputted by the owner reservations - table of all completed reservations: • vehicle_id: vehicle's unique ID • reservation_type: 1 is Hourly rental, 2 is Daily, 3 is Weekly Using the two attached datasets, please prepare a short presentation with your answers to the following questions: • Which of the factors seem to be most important in driving total # of reservations for our vehicles? (technology type, pricing, number of car photos, street parking, car description length) • How does the car's technology type seem to affect reservations? Feel free to use any tool(s) that you feel comfortable with to complete this analysis (Excel, SQL, R, Python, etc).

Find significant factors determining car rental