EMAGIN Clean Technologies Data Scientist Interview Questions | Glassdoor

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EMAGIN Clean Technologies Data Scientist Interview Questions

Interviews at EMAGIN Clean Technologies

2 Interview Reviews

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Data Scientist Interview

Anonymous Interview Candidate
No Offer
Negative Experience
Average Interview

Application

I applied online. The process took 6 weeks. I interviewed at EMAGIN Clean Technologies in February 2019.

Interview

The interview process initially seemed organized with a web based interview and then in-person interview with the data science lead. The interviewing panel was younger (early to mid 20s) and the data science lead did not seem to possess enough knowledge in her field. A case study was handed over to solve, post in person interview and asked to submit in a week. There was no response to the queries on the case and before and after submission, I had to follow up to get feedback on the submission. It seems the entire team was going through a very hectic schedule in meeting the needs of a newly acquired client and working over weekends on this. Finally, I was declined offer after another round of follow up. The entire process was very disorganized as they did not seem to value the time of the candidates. They did not even care to formally take a feedback after 3 rigorous rounds of interview. I would personally not suggest any candidate to apply for any openings in this start up.

Interview Questions

  • Basic questions around ML, DL and some specific questions that you must answer what they wish to listen as the lead wont be able understand if you start getting into the depth and may think you would be a possible threat to her position.   1 Answer

Other Interview Reviews for EMAGIN Clean Technologies

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    Data Scientist Interview

    Anonymous Interview Candidate in Waterloo, ON (Canada)
    No Offer
    Positive Experience
    Average Interview

    Application

    I applied online. The process took 4+ weeks. I interviewed at EMAGIN Clean Technologies (Waterloo, ON (Canada)) in May 2019.

    Interview

    HR phone screening, take-home technical test, in-person interview (1-2 hours), data science case study (or take-home test), final interview. The whole process took about a month.

    The technical test was an exercise in the use of pandas for time series data. The data science case study had a time series forecasting problem (imputing nans, accounting for seasonality, exogenous features, etc.) and a control systems optimization problem (just need to explain your approach). Very relevant to the job so they put a good amount of thought into it.

    Interview Questions

    • Explain what is different about evolutionary algorithms compared to other optimization algorithms   Answer Question
    • How do you build a time series forecasting model using machine learning?   Answer Question
    • Explain the bias-variance trade-off in the context of decision trees and ensemble tree methods.   Answer Question
    • Explain why MIMO models are more accurate than MISO models for forecasting more than one time step in the future   Answer Question
    • How do you evaluate model performance?   Answer Question

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