The coding test had to do with simple concepts in algorithms and machine learning, while the 1-1 interviews were of a broader scope where we discussed standard tools and concepts in data science, as well as broader aspects of collaborative research work.
1. 1st round involves question related to projects and earlier experience. 2. 2nd round is to develop model to classify for a given geolocation the position has rooftop or not. 3. Theoretical question simple based on performance metrics like F1 score, precision, recall, MAD which were used in my projects.
The assignment was a real estate price prediction problem ,they ask you to provide insights and do Machine learning to predict the price of units in Greece . Here when I really became disappointed , the data science consultants ( or who claim they are) who interviewed me lacked basic intuitive knowledge about data science , questioned the why behind creating a simple benchmark to validate ML models on . They also seem that they didnt try to solve the problem before they gave out to candidates , which made them unaware of the aspects of the problem
Standard questions for such positions! SQL, Statistics, AB-design, Time Series, Data Engineering
Previous experience in similar projects
- ML Modelling problem - Talk about a recent data science project you have worked on
No technical or hard questions. They asked me to talk about the major projects that I've been working on.
How would you calculate the cost of a missed shipment?
What is funneling method in marketing.
sql query for joining 3 tables with duplicates and cte with some interval chaining logic
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