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Hybrid Data Scientist - ML & Predictive Analytics

Touch 'n Go Group

Kuala Lumpur

Hybrid

MYR 60,000 - 80,000

Full time

Today
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Job summary

A leading fintech organization in Kuala Lumpur is seeking a Data Scientist to develop predictive models and implement machine learning solutions. You will analyze large datasets and provide insights to drive business impact while collaborating with project teams to ensure timely delivery. Ideal candidates should have a Bachelor's degree in a quantitative field and 1-2 years of experience in quantitative analytics. The position offers a hybrid work model with benefits including medical coverage and a flexible work schedule.

Benefits

Hybrid and Flexi hours
eWallet meal allowance
Unlimited office pantry fruits, snacks and drinks
Mobile and broadband reimbursement
Outpatient medical benefits for dependents
Additional family leave
Comprehensive medical coverage
Corporate membership discount

Qualifications

  • 1 - 2 years of experience in quantitative analytics or data modeling.
  • Deep understanding of clustering and classification techniques.
  • Familiarity with Big Data frameworks.

Responsibilities

  • Contribute to the development of predictive and prescriptive models.
  • Analyse large-scale structured and unstructured data.
  • Support model optimisation and deployment.

Skills

Predictive modeling
Machine learning
Data analysis
Statistical analysis
Python
SQL

Education

Bachelor's degree in Quantitative Field

Tools

Tableau
Hadoop
Spark
Job description
A leading fintech organization in Kuala Lumpur is seeking a Data Scientist to develop predictive models and implement machine learning solutions. You will analyze large datasets and provide insights to drive business impact while collaborating with project teams to ensure timely delivery. Ideal candidates should have a Bachelor's degree in a quantitative field and 1-2 years of experience in quantitative analytics. The position offers a hybrid work model with benefits including medical coverage and a flexible work schedule.
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