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Manager, Data Scientist – Advanced Analytics & Predictive Modelling

SpringCube

Full time - Manager

Insurance & InsurTech

Singapore ( Hybrid )

Published 4 weeks ago

Salary: SGD10,000 - SGD15,000

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position above to find your next career move.

Manager, Data Scientist – Advanced Analytics & Predictive Modelling

Company Overview
A leading pan-Asian life and health insurance organization serving over 12 million customers across 10 markets. This company focuses on delivering innovative, customer-centric, and digitally enabled solutions that redefine the insurance experience. Established in 2013, the organization is committed to making insurance simple, accessible, and relevant in some of the fastest-growing markets in the world.

Job Description
The Manager, Data Scientist will independently manage end-to-end analytics and predictive modelling projects. This role involves conducting advanced analytics, leveraging artificial intelligence to improve modelling accuracy, and generating actionable business insights. The position requires expertise in statistical modelling, machine learning, and data integration to support data-driven decision-making across the organization.

Key Responsibilities

  • Manage analytics and predictive modelling projects from end to end.
  • Conduct data sourcing, integration, discovery, and transformation.
  • Design modelling methodologies tailored to business needs.
  • Build, test, and execute models to achieve optimal outcomes.
  • Perform model reviews, optimization, and ensure effective execution.
  • Use advanced analytics and artificial intelligence to enhance model accuracy.

Qualifications

  • Education: Bachelor’s or Master’s degree in Statistics, Information Engineering, Computer Science, or Mathematics.
  • Certifications: SAS and Machine Learning certifications (preferred).
  • Experience: Over 5 years of experience in data analytics, statistical modelling, or machine learning.

Skills & Knowledge

  • Modelling Expertise: Linear regression, logistic regression, decision trees, neural networks, random forest, k-means clustering, ARMA, and association rules.
  • Tools & Technologies: Proficiency in SAS, SPSS, R, Python, RapidMiner, Spark, pylearn2, and SQL.

Disclaimer: SpringCube curates tech job listings from various company websites to support tech professionals in Singapore during these challenging times.

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