First VP/VP, Data Analytics, Group Wholesale Banking

United Overseas Bank

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Job summary

United Overseas Bank is seeking a senior data analytics professional to lead large-scale analytic projects across corporate spaces, with emphasis on anti-financial crime and AML. The role requires deep ML/NLP expertise and hands-on coding in Python/SAS/R, with experience in big data tools like Hadoop and Spark.

You will collaborate with cross-functional stakeholders to transform data into actionable insights and drive business impact within a top-tier banking environment in Singapore.

Qualifications

  • 7+ years of data analytics/science experience with ML/NLP/OR
  • Hands-on with Python/SAS/R and Hadoop/Spark
  • Strong problem solving and financial industry knowledge, with good communication and collaboration

Responsibilities

  • Lead large-scale analytic projects in corporate space focusing on AFC/AML.
  • Analyze macro and micro data to answer business questions using strategic analysis and ML/NLP models.
  • Coordinate with internal/external stakeholders to ensure data-to-insights conversion and implementation of insights

Skills

Data analytics
ML/NLP
Python
R
SAS
Stakeholder management
Communication

Tools

Hadoop
Spark
SQL
SAS

Job description

Company: 1011 United Overseas Bank Ltd

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

Job Description

The Wholesale Bank function operates a dynamic business model that provides financial services and solutions to help our clients achieve their strategic business objectives. Our mission is to become the premier-provider of banking services and solutions for Asia-based commercial banking companies (small medium enterprises), large corporations, financial institutions as well as multinational corporations. Our coverage teams work in full alignment with specialised teams across Transaction Banking, Investment Banking, Global Markets and Group Retail to deliver seamless solutions to our clients.

Job Responsibilities
  • Lead large scale analytic projects in corporate space to drive for business impact with a focus on AFC/AML
  • Analyze macro and micro data (structured/less structured) to answer business questions via strategic analysis, machine learning/NLP models.
  • Coordinate with various internal and external business stakeholders to ensure smooth data-to-insights conversion and the necessary of the insights implementation
Job Requirements
  • At least 7and above years' solid data analytics/science experience, deep technical expertise on ML/NLP/OR, with hands-on capability, Python/SAS/R, Hadoop/Spark
  • Excellent problem solver, good understand of financial industry knowledge, consulting experience is a plus
  • Strong sense of responsibility and teamwork
  • Good communication and interpersonal skills to effectively interact with internal and external stakeholders of all levels
Additional Requirements

Be a Part of the UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.

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