Vice President, Aml/financial Crime Data Analyst

4 days ago


Central Singapore Emprego SG Full time

**Location**

Singapore, Central Singapore

**Job Type**

**Date Posted**

32 minutes ago

Additional Details

**Job ID**

1128

**Job Views**

3

**Job Description**:
Job Responsibilities

**Responsibilities**:

- Develop new and enhance / fine-tune existing screening and detection models in the areas of onboarding, transaction monitoring and ongoing customer reviews. The expected outcome of these models is proactive identification and prevention of high risk prospects / customers and illicit activities, including new and emerging typologies
- a suite of statistical / data science techniques (regression, gradient boosted trees, network analytics, neural networks, NLP, audio/image processing, etc) that is best fit for purpose / use
- both structured and unstructured data (test, audio, image, streams, etc) that can be found within the bank and external partners, vendors or in the internet in general (social media, web-crawled data, etc)
- Own and manage UOB’s business intelligence tool / dashboard (ie, Qliksense). This include managing the data cube and maintaining / creating new dashboards for users within Group Retail. You may also be required to provide reports or ad-hoc analyses using other means (eg, SAS)
- Support any data management / engineering activities related to AML - eg, procuring, ingesting/preparing data (including unstructured) from UOB’s datalake to datamarts/cubes, and ultimately for consumption in predictive models or dashboards
- Conduct / support any UAT or other testing of data, systems, tools related to AML/compliance
- Frequent and regular discussions with front-line teams (to understand new typologies, identify requirements, etc), group and business compliance teams, integrated fraud management teams, technology teams, etc to solution and implement assets / use cases to address AML, compliance and financial crime objectives

**Qualifications**:

- 5 years of experience in data science as applied to AML/fraud/financial crime
- Undergraduate degree in a quantitative programme, such as Statistics, Mathematics, Actuarial Science, Financial Engineering, etc. MBA / post graduate degree is an added advantage
- Very strong programming + technology skills:

- SAS is a must for data management, ad-hoc analyses and modelling. Python is used for most newer/advanced algorithms and data science libraries
- Cloudera Big Data Platform - for data engineering and data science work on UOB’s data lake
- Qliksense - to build/enhance/maintain QVD cube and dashboards for business / non-technical users
- MS Office macro programming for automation
- Analytical mind with sound business insight, excellent communicator (verbal and written), highly meticulous, and self-motivated
- 5 years of experience in data science as applied to AML/fraud/financial crimeUndergraduate degree in a quantitative programme, such as Statistics, Mathematics, Actuarial Science, Financial Engineering, etc. MBA / post graduate degree is an added advantageVery strong programming + technology skills:
The Credit and Risk Management function is comprised of three teams: Risk Management, Credit and Special Asset Management. We manage the risks arising from the Group’s business activities within the risk appetite established by the Board. This involves identifying and evaluating the risks, developing effective risk governance and strategies as well as providing independent assessment of the overall risk profile.Be a part of UOB Family

Tags

vice

president

amlfinancial

crime

data

analyst

risk

and

decision

management

group

retail



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