Assistant VP, Regional Data Modeler, Gp Compliance

United Overseas Bank Limited (UOB); Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading Asian bank in Singapore seeks an experienced data professional to develop and implement advanced analytical models, improve processes based on data insights, and present findings to senior management. The ideal candidate holds a Bachelor's in a relevant field with significant experience in the tech industry, particularly in data roles. Proficiency in Python and machine learning tools is essential. This role offers an opportunity to make a substantial impact in a dynamic environment.

Qualifications

• 5–10 years of experience in the tech industry.
• 3–5 years of experience in data engineering, analysis, or science.
• Strong understanding of statistical analysis and machine learning algorithms.

Responsibilities

• Develop and implement advanced statistical models.
• Collaborate with teams for process improvement based on data.
• Present findings to senior management.

Skills

Python/Spark proficiency

Machine learning libraries (scikit-learn, TensorFlow)

Data engineering tools (Hive/Impala, Oozie, Hadoop)

Statistical analysis understanding

Model deployment and scaling experience

Excellent communication skills

Team collaboration

Education

Bachelor's degree in Computer Science, Statistics, Mathematics or related field

Master's degree preferred

Tools

scikit-learn

TensorFlow

Hive

Impala

Oozie

Hadoop

Job description

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 Responsibilities

• Develop and implement advanced statistical models to analyze large datasets.
• Collaborate with cross‑functional teams to identify opportunities for process improvement based on data analysis.
• Present findings and recommendations to senior management in clear and concise reports.
• Stay updated with the latest advancements in data science and machine learning techniques.

Job Qualifications

• Education: Bachelor's degree in Computer Science, Statistics, Mathematics or related field; Master’s preferred.
• Experience: 5–10 years of experience working in the tech industry and 3–5 years of experience in a data engineering and/or data analysis or data science role, ideally in the financial services industry.
• Skills:
  • Proficiency in Python/Spark to code complex data engineering use cases.
  • Experience with machine learning libraries such as scikit‑learn, TensorFlow.
  • Experience in data engineering tools such as Hive/Impala, Oozie, Hadoop, etc.
  • Strong understanding of statistical analysis and machine learning algorithms.
  • Experience in deploying and scaling ML/AI models.
• Excellent communication skills, both written and verbal.
• Ability to work independently and as part of a team.

Additional Requirements

Develop, Engage, Execute, Strategise, University‑Bachelor - Data Science & Analytics

Be a Part of the UOB Family

Equal Opportunity Employer

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.

Apply now and make a Difference

Apply now and make a difference.