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Senior Vice President/Vice President, Data Scientist (Team Lead), Data Chapter

SpringCube

Full time - VP/GM/C-level

Banking & Financial Services

Singapore ( Onsite )

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 below to find your next career move.

Company Overview

A leading financial institution in Asia, focused on driving strategic transformation and innovation through advanced analytics and research. The organization’s Data Chapter aims to foster synergy among data analytics functions, establish centers of excellence, and cultivate a strong community for data professionals.

Job Description

Senior Vice President/Vice President, Data Scientist (Team Lead), Data Chapter

Job description

  • Lead a team of data scientists within the Data Analytics Centre of Excellence to deliver AIML (Artificial Intelligence and Machine Learning) solutions that support the bank’s strategic priorities across consumer banking, private banking, and institutional banking.
  • Collaborate with various data chapters and business stakeholders to drive revenue growth through the implementation of AIML across different units within the horizontal organizational structure.
  • Develop and implement a comprehensive AIML roadmap for the bank, fostering synergy between diverse business products and units from a holistic perspective.
  • Identify and prioritize business opportunities where AIML can play a pivotal role.
  • Enhance the transparency of AIML capabilities and promote an AIML culture throughout the organization.
  • Provide expert advice on AIML applications to data users and business owners.

Requirement

  • Degree or above in mathematics, statistics, information science, physics, or related disciplines, with a minimum of 8 years of work experience in machine learning and modeling, including at least 3 years in a managerial role.
  • Strong business acumen with the ability to address business needs and identify business opportunities.
  • Hands-on experience in AI, machine learning, and modeling, with a proven track record of implementing AIML to drive business impact.
  • Comprehensive understanding of the data science production life cycle, with demonstrable experience working with structured, semi-structured, and unstructured data.
  • Excellent software skills (Python, SQL) and knowledge of design patterns and code optimization.
  • Familiarity with software development best practices and tools (Agile, TDD, Jira, Jenkins, Git).
  • Banking business domain knowledge is a plus.

Disclaimer

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