Machine Learning Intern, Data Analytics Machine Learning

Department: HOT HK
Salary: $20K-25K HKD per month

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RECRUITER SUMMARY

HOT_HK Data Scientist, Machine Learning Intern, Data Analytics Machine Learning, $25K HKD per month

29/02/2024

Candidate Background

Nationality:
Hong Kong PR
Residence:
Hong Kong
Education:
Bachelor of Science, Data and System Engineering XXXX
Languages:
English – Fluent, Cantonese – Fluent, Mandarin – Fluent
Experience:
1+ years of experience in the industry Current & Previous Employers and jobs include: Machine Learning Intern at XXXX, AI and Data Engineer Intern at XXXX
Motives:
Is actively looking for a job right now because will graduate in June. Open for data-related jobs (Engineer, Scientist, Analyst)
Current Salary:
–
Expected Salary:
$20K-25K HKD per month
Notice Period:
3 Months
Interview Availability:
Requires a day notice

Interview Assessment Notes

    1. Could you introduce yourself and tell us about you? Your current / recent jobs and employers? Previous companies and jobs?
      He has worked with XXXX before as a Machine Learning Intern where he assisted the team in doing lots of machine learning projects and data analysis tasks; he has used NLP and different machine learning techniques in here. Before this, he was with XXXX as an AI and Data Engineer Intern where he almost did the same in Hang Seng, the only difference is that he needs to monitor a large scale database on AWS cloud.
    2. What skill(s) / experience would you self-describe as strongest or specialist in?
      Strongest skill would be machine learning and data analytics skills. For the technical side, he is good with Python, different machine learning frameworks, and data processing tech stacks as well. Rates himself a 3.5-4 out of 5 in Python since he still has lots to learn in this field.  
    3. Do you have the lists of key criteria’s according to the clients’ requirements?
      Has 1+ years of internship experience in the data side. Proficient with Python, has experience with C++ and JavaScript. Mostly familiar with PostgreSQL, AWS database, Azure Cloud database. Familiar as well with building automated data pipelines and mapping across databases. Good with AWS, Azure, and Google Cloud Platform.  

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