Senior Analyst - Decision Science - Credit Risk

Posted 01 August 2022
Salary Negotiable
Job type Permanent
DisciplineRisk & Analytics
Contact NameKym Lawler

Job description

Senior Analyst - Decision Science - 50k-60k

Are you feeling stuck and are looking for a new challenge?

Are you ready to take a leap into a role that will empower you to achieve great things?

Are you looking to join a leading Irish Bank?

Your role:

  • Develop and analyse models to quantify credit loss.
  • Develop data-driven and predictive models across Probability of Default (PD), Loss Given Default (LGD), Exposure of Default (EAD) and State of the Economy (SOE) models.
  • Utilise traditional statistical techniques and apply mathematical theory/concepts.
  • Build large datasets that are robust and efficient for use across Decision Science helping to maximise speed of development through efficient coding and automation.
  • Produce high quality 'value-add' analysis and insights across data mining and trend analysis and develop optimum segmentation strategies.
  • Communicate findings and insights gathered through model development to the Decision Science management team and internal partners.
  • Support the team through delivery of relevant deep dive analysis and model remediation actions originated from internal and external stakeholders (i.e. Model Validation Team, Auditors, Central Bank of Ireland etc.).
  • Mentor and guide junior modellers/analysts to deliver the Bank's Credit Risk model development agenda.

If you have the below experience, you're likely to be suitable;

  • 2+ years' experience working as a risk analyst, model developer, business analyst, data scientist or data analyst.
  • Experience and knowledge of programming languages such as SAS (Base, Guide, Miner), SQL or other advanced statistical/econometric analysis software.
  • Knowledge of statistical techniques (such as regression, time series, decision trees, scorecards, experimental design etc.).
  • Excellent analytical, problem-solving and communication skills with proven skills in summarising and interpreting large volumes of data and translating into meaningful insights.

If this sounds like the job for you, please feel free to reach out to me to discuss it further.