1. JOB HOLDER & JOB DETAILS:
AML Tuning & Data Analyst
VP, Head of AML Tuning & Data Analytics
Compliance Technology, Data & Reporting
Prepared / Revision
2. JOB PURPOSE:
To perform data analytics & data engineering activities including and not limited to threshold tuning, identification of new customer transaction and patterns using big data tools uncovering new AML themes and AML risk typologies to improve the alert quality and improve alert to STR ratio.
3. JOB DIMENSIONS:
Revenues / Budget:
4. KEY ACCOUNTABILITIES:
Job Specific Accountabilities
To encourage and impart knowledge on the compliance staff in the Compliance technology unit to ensure good and efficient productivity besides timely delivery. And to ensure that the team is aligned with the Group/department objectives
Policies, Systems, Process & Procedures
Follow all relevant departmental policies, processes, standard operating procedures, and instructions so that the work is carried out in a controlled and consistent manner.
Support the Compliance Technology, Data and Reporting Department in identifying continuous improvement and sustainability improvement opportunities for the related systems, processes and practices.
Manage the implementation of the AML Group compliance systems Road map as agreed with the Compliance management and keep Project Lead & Head of Compliance Technology, Data and Reporting updated.
Ensure & Manage proactive steps are taken to work with Group IT and other stakeholders of the compliance system projects to ensure fit for business compliance AML systems are designed.
Manage all relevant AML compliance system changes required in the SAS Financial Crime Analytics platform as per business requirements setting timelines, creating programme structures and installing/updating systems architecture where appropriate to support compliance capabilities for major changes.
Exceptional technical writing skills.
Ability to communicate complex data in a simple, actionable way.
Ability to visualize data in the most effective way possible for a given project or study.
Analytical and problem-solving skills.
Ability to work independently and with team members from different backgrounds.
Excellent attention to detail.
Proficiency in the below set of Technologies in line with the roles.
SAS (SAS EG, SAS e-Miner, SAS DI Studio, SAS Data Flux, SAS Viya, Base SAS)
Data Engineering & Analytics.
Identifying relevant data sources for business needs
Collecting & Integrating structured and unstructured data.
Sourcing missing data.
Enhancing the data collection process.
Processing, cleansing & verifying of data.
Organizing data in-to usable formats.
Data engineering – build pipelines.
Data exploration techniques
Building predictive models using Supervised and Unsupervised Models.
Building machine learning algorithms.
Analysing data for trends and patterns and to find answers to specific questions.
Setting up data infrastructure.
Develop, implement and maintain databases.
Assess quality of data and remove or clean data.
Generating information and insights from data sets and identifying trends and patterns.
Preparing reports for executive and project teams.
Create visualizations of data
Collaborate with Compliance SMEs to develop Compliance related MI dashboards.
Develop periodic reporting plan and maintain the schedule and workflow for multiple reports.
Collaborate with Compliance colleagues to obtain information on functional trends to refine, re-tune and build new Analytical models
Submit Analytical dashboards/newsletters to team lead for review and circulation to Compliance stakeholders.
5. Job Context
(Specific accountabilities unique for the role which are not covered in Section 4)
TO BE LEFT BLANK
6. FRAMEWORKS, BOUNDARIES, & DECISION MAKING AUTHORITY:
FUNCTIONS WITHIN THE FRAMEWORK AND BOUNDARIES OF GROUP POLICIES AS WELL AS OVERALL ORGANISATIONAL AND GOVERNANCE FRAMEWORKS.
AUTHORISED TO TAKE DECISIONS AS PER THE APPROVED AUTHORISATION MATRIX.
GROUP/LOCAL LEVEL ROLE (BANK TO CONFIRM)
7. QUALIFICATIONS & EXPERIENCE:
Bachelor’s degree in computer science/technology & Financial Crime systems.
At least 5 years of experience in risk analysis, data analytics or relevant statistic discipline
At least 1 year of experience in an financial crime compliance role
Has relevant experience of data management, AI, MLtools and AML compliance systems