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SAS Analyst - Energy Markets & Risk Forecasting

Connect Executive Resourcing Limited

North East

On-site

GBP 35,000 - 48,000

Full time

10 days ago

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Job summary

A large energy business in North East England is seeking an experienced numerical analyst to provide insight via SAS analysis. Responsibilities include monitoring credit risk performance and developing proposals based on data analytics. Ideal candidates will have a strong academic background, experience in SAS analytics, and knowledge of the domestic energy sector. This position offers an excellent opportunity for data-driven individuals looking to influence credit risk strategies.

Qualifications

  • Strong academic background with a numerical/statistical/science based degree.
  • Highly numerate with strong data analysis experience.
  • Experience with SAS analytics is essential.
  • Risk acquisition or portfolio risk experience ideal.
  • MI report production and development experience.
  • Macro-economic analysis and statistical model development experience ideal.
  • Experience in the domestic energy retail sector is highly advantageous.

Responsibilities

  • Monitor and evaluate the performance of policy rules and scorecards.
  • Develop and maintain regular MI to monitor credit risk KPIs.
  • Identify changes needed in credit strategies and data acquisition.
  • Work with colleagues to implement new credit risk capabilities.

Skills

Data analysis
SAS analytics
Statistical modeling
Macro-economic analysis

Education

Numerical/statistical/science based degree

Tools

SAS
SQL
Python
C++
Job description
A large energy business in North East England is seeking an experienced numerical analyst to provide insight via SAS analysis. Responsibilities include monitoring credit risk performance and developing proposals based on data analytics. Ideal candidates will have a strong academic background, experience in SAS analytics, and knowledge of the domestic energy sector. This position offers an excellent opportunity for data-driven individuals looking to influence credit risk strategies.
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