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Senior Data Scientist

Hong Kong
R

Randstad

Startup
Category
Technical
Experience
8+ years
Type
Full-Time
Location
Hong Kong
Job Description
Benefits & Culture
Flexible hours
Remote work
Paid time off
Fast-paced environment
Direct feedback
Growth opportunities
This goes straight to the founder
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No recruiters. Founders reply directly.

Founder Signals
Response Rate
85%
Avg Response Time
2 hours
Compensation Calculator
In startups, higher salary usually means lower equity.
Salary (affects equity %)
Link salary ↔ equity
$125,000
$80,000$70,000
Equity % (auto from trade-off model)
0.51%
0%5%
Projected Exit Value
$350,000,000
$10M$500M
Live Trade-off
Salary
Equity %
Est. Equity Value at Exit
$100,000
0.51%
$892,500
$125,000
0.51%
$892,500
$150,000
0.51%
$892,500
$175,000
0.51%
$892,500

Advanced Salary & Equity Calculator

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About the Company

The hiring company is an established financial institution looking to hire an experienced data scientist to join their team and provide innovative tech-savvy solutions for business and operations.

About the Job

  1. Develop and implement advanced analytics and machine learning solutions to enhance business strategies. This includes working with various data types, such as browsing data, voice recordings, emails, and images.
  2. Integrate a wide range of customer data, both internal and external, to create a comprehensive, 360-degree customer view.
  3. Assess existing system capabilities and identify necessary system and process developments. Plan and execute business applications with realistic timelines by leveraging internal banking systems and third-party vendor solutions.
  4. Act as a Subject Matter Expert to train and promote a strong machine learning culture among other analysts.
  5. Establish a continuous learning loop to ensure that insights and knowledge are applied for ongoing enhancement.

Skills and Experiences Required

  1. Bachelor's or Master's degree in Computer Science, Data and Information Management, Statistics, or a similar field is required.
  2. 7-10 years of hands-on experience as a data scientist is necessary, with a focus on developing and executing large-scale analytics projects within the Financial Services Industry.
  3. Proficient in Python and SAS. Experience with data manipulation, analysis, machine learning, web crawling, and Natural Language Processing (NLP) is essential.
  4. Possess a strong ability to translate analytical concepts into effective business strategies and applications that drive business value.
  5. Demonstrates a high degree of ownership and a service-oriented mindset.
  6. Committed to continuous learning and staying updated with the latest advancements in data science and machine learning.
  7. Proficient in English and Chinese (both Cantonese and Putonghua)