Data Scientist, Data Analyst, Machine Learning Models

Department: HOT HK
Salary: $23K-28K HKD per month

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RECRUITER SUMMARY

HOT_HK Data Scientist, Data Analyst, Machine Learning Models, $28K HKD per month

23/02/2024

Candidate Background

Nationality:
Hong Konger
Residence:
Canada
Education:
Master of Science in Data Science XXXX, Bachelor of Engineer in Bioengineering XXXX
Languages:
English – Fluent, Mandarin – Fluent, Cantonese – Fluent
Experience:
2+ years of experience in the industry Current & Previous Employers and jobs include: Data Analyst at XXXX, Data Analyst at XXXX    
Motives:
Is actively looking for a job right now because currently not engaged with anything. Open for Data Engineer role.
Current Salary:
$23K HKD per month
Expected Salary:
$23K-28K HKD per month
Notice Period:
Can start immediately
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?
    She has worked for two companies as a Data Analyst: XXXX and XXXX. In XXXX, she mainly focuses on event tracking, user behaviour, and engagement time to generate data report to draw different data insights to present to her supervisors. Back in XXXX, she is mostly handling digital marketing campaigns for her clients where she also did event tracking data generation.
  2. What skill(s) / experience would you self-describe as strongest or specialist in?
    Strongest skill would be her skills in drawing data from unstructured data and can also use data patterns to make some data direction. She is also good with machine learning models and uses transformer models or GPT models.
  3. Do you have the lists of key criteria’s according to the clients’ requirements?
    Has about 1-2 years of experience when it comes to data engineering/data analytics. She usually uses Python to make data models and AI models, currently learning JavaScript online. Familiar with building automated data pipelines. For databases, she mostly uses MongoDB, SQL, and other DB to generate data. Good with both Azure and GCP.

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