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Financial Crime Risk Analyst

  • Kraków, małopolskie pokaż mapę
  • Specjalista
  • 23.07.2017

Pracodawca ma prawo zakończyć rekrutację we wcześniejszym terminie.

Global Risk Analytics (GRA) is a global team covering all risk types and is accountable for model risk in HSBC. To name a few, it covers credit risk, market risk, traded risk, counterparty credit risk, anti-money laudering, sanctions, anti-bribery and corruption, conduct risk, operational Risk. GRA is tasked with setting policy and standards, and providing cutting-edge tools to help identify, measure and manage risk, and ensure compliance across HSBC group-wide. This applies to both internal models as well as models also used for external reporting purposes. In our approaches, we apply models used in many different areas of applied research, including machine learning, bio-tech and aerospace engineering, supported by applying the latest techniques in data analytics, prototyping, visualisation approaches and infrastructure.

Having one analytics team spanning all risk types means that we are able to share best practice and drive innovation by bringing together competence from across different areas. Being part of a global team in one of the largest banks is also an opportunities for talented analysts to build careers across a range of disciplines.

Financial Crime Risk Analyst
Location: Kraków
Ref No: GRA/FC/Risk/A/07/2017


This is a role responsible for supporting the development and maintenance of collateral models and methodologies for traded risk measurement. 

Key Accountabilities: 

  • Enable The Bank to consistently assess inherent Financial Crime Risk of countries, banking products and customers, by providing sound and transparent quantitative methodologies
    in support of the Bank’s Financial Crime Risk Management Models.
  • Ensure due observance of HSBC Internal Control Standards and Global Risk & Compliance, including the timely implementation of recommendations made by internal / external auditors and external regulators.
  • Develop and oversee of the risk and control framework around FC Risk model development, ensuring that appropriate data, statistical techniques, scientific standards and business processes are in place.
  • Promote of a culture of data driven decision making, aligning short term decisions and investments with longer term vision and innovative objectives.

Requirements: 

  • Postgraduate degree in Mathematics, Statistics, Physics, Data Science, Computer Science, Engineering, Economics or relevant quantitative discipline.
  • 1 - 3 years of post-qualification experience in a data-driven discipline is desired.
  • Deep understanding of Statistics, Probability theory and Linear Algebra a must.
  • Strong coding skills in at least two of the following: VBA, R, SAS, Matlab, Python, Spark, SQL, Hive a must.
  • Familiarity with the Hadoop stack is highly desirable.
  • Familiarity with relational database technologies and concepts is highly desirable.
  • Should be adept in using MS Office with exceptional MS Excel Skills.
  • Experience and Exposure to visualization technologies such as Qlikview/ Spotfire will be an added advantage.
  • Familiarity of Anti-Money Laundering and Financial Crime Compliance framework is a plus but not required.
  • Must be fluent in English.

We offer: 

  • Stable job in professional team.
  • Interesting path of career in an international organization.
  • Consistent scope of responsibilities.
  • Private health care, employees’ benefits.
You'll achieve more when you join HSBC.
 
All current positions are available on: http://www.hsbc.com/careers
 
To apply for this position please send your curriculum vitae in English
including reference number, using "Apply now" button below.

We thank all interested candidates for their applications. We reserve the right to contact only selected candidates. Only those applications that include the candidate's consent to process personal data by HSBC Service Delivery (Polska) Sp. z o.o., in accordance with the Data Protection Act as of 29 August 1997 (Journal of Acts of 2002, No 101, pos. 926 with later amendments) will be considered.

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