Assistant VP, Regional Data Modeler, Gp Compliance

UOB; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

UOB is seeking an experienced data scientist in Singapore to develop and implement advanced statistical models and analyze large datasets. The ideal candidate will have a Bachelor's degree in a relevant field, with a preference for a Master's, and 5-10 years of tech industry experience, including 3-5 years specifically in data engineering or data science. Proficiency in Python/Spark and familiarity with machine learning techniques such as TensorFlow are crucial. The position also offers opportunities for professional development in the dynamic financial services sector.

Qualifications

• 5-10 years in the tech industry.
• 3-5 years in data engineering, analysis, or data science, ideally in financial services.

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.

Skills

Proficiency in Python/Spark

Machine learning libraries such as scikit-learn, TensorFlow

Data engineering tools like Hive/Impala, Oozie, Hadoop

Statistical analysis and machine learning algorithms

Deploying and scaling ML/AI models

Excellent communication skills

Ability to work independently and as part of a team

Education

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

Master’s preferred

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 in the tech industry and 3 – 5 years in data engineering, analysis or data science, ideally within financial services

Skills:

• Proficiency in Python/Spark for 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 Statement

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.