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Financial Crime Data Analytics - Assistant Manager

Date: Oct 16, 2021

Location: London, United Kingdom

Company: KPMG UK

The Team

The Financial Crime Technology team sits within KPMG's Risk Consulting Function, working within our Forensic practice.

The candidate will be required to work closely with our clients, typically large financial institutions, on the challenges with their financial crime compliance obligations. As such, the candidate will be expected to possess a variety of technical skills and knowledge of the market.

Our specialisation is data analytics in the financial crime space. The role will involve interactive scoping workshops with clients to identify engagement requirements, creating detailed project plans, analysing both structured and unstructured data, understanding relevant legislation in order to assess clients’ policies, procedures and organisational risk, and forming logical conclusions and solutions in order to provide sound advice. A full list of required technical and soft skills is provided under the ‘Qualifications, Skills and Experience’ section.

The Role
The role gives an opportunity to work with many areas of the business, from technical SMEs through to the consulting side in the wider Forensic practice. Furthermore, the role will offer the chance to develop the skills required for progression; the candidate will therefore be expected to present their work to both clients and the team internally.

The Person
This exciting role will fully utilise your existing programming, data analysis and data management skills. Strong technical skills are essential as you will be required to develop solutions either individually or as part of an integrated multi-disciplinary team.

- Experience with SQL: functions, stored procedures, pivoting, cursors, recursion, CTEs, triggers, dynamic SQL, query optimisation, transactions and XML.
- A working knowledge of database architecture, specifically designing and reviewing data storage structure, database normalization (1NF, 2NF, 3NF etc) and ensuring these structures are fit for purpose and scalable.
- Good understanding of using Python including its built-in functions and knowledge of data manipulation packages.
- Proven experience in automating manual tasks and ETL.
- Experience using any version control system (e.g. Git or CVS).
- Knowledge of full stack development in any programming/scripting language.
- Basic understanding of working with or building an API (REST)
- Ability and curiosity to conduct root-cause investigative work in relation to a system’s performance, configuration or data flow issues.

- Knowledge of statistical techniques and analysis (such as regression, clustering, sampling and social network analysis).
- Experience in cloud-based deployment (e.g. Azure, GCP or AWS)
- Applied knowledge of machine learning and cognitive computing.
- A functional understanding of international sanctions, regulations and anti-money laundering protocols.

- Excellent communication skills with the ability to explain complex technical analysis to a non-technical audience.
- Tenacious problem solving attitude: the ability to identify and fix issues before they become critical.
- Independent worker: you are reliable and can be trusted to deliver high-quality work with minimal oversight.
- Self-review system: you use a structured approach to ensure that your deliverables would require only minor review points from a stakeholder.

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