SAS Credit Risk Analyst – Energy Markets

Connect Executive Resourcing Limited; North East; On-site; GBP 40,000 - 60,000; Full time

Job summary

Connect Executive Resourcing Limited is seeking an experienced numerical analyst in North East England to enhance their credit risk teams. The ideal candidate will be responsible for monitoring and evaluating credit risk performance, developing MI to support credit strategies, and implementing new credit risk capabilities using SAS analytics.

Candidates should possess a strong academic background in a relevant numerical field, experience with SAS and data analysis, and knowledge of the energy retail sector is a plus. Apply now to join this dynamic energy business!

Qualifications

• Strong academic background with a numerical/statistical/science based degree.
• Highly numerate with strong data analysis experience.
• Experience with SAS analytics is essential.

Responsibilities

• Monitor performance of policy rules and scorecards.
• Evaluate credit risk performance and optimize decisioning.
• Develop MI for credit risk KPIs and strategies.
• Maintain credit loss forecasts.
• Change credit strategies using data analytics.
• Estimate credit loss assumptions for proposals.
• Design data tables for analytics efficiency.
• Define requirements for new credit risk capabilities.

Skills

Numerical analysis

SAS analytics

Data analysis

Statistical model development

SQL

Python

C++

MI report production

Education

Numerical/statistical/science-based degree

Job description

A large energy business in North East England is currently seeking an experienced numerical analyst to join their expanding credit risk teams to provide insight and support via SAS analysis. Key responsibilities:

• Monitor and evaluate the performance of individual policy rules, cut-offs, scorecards and champion challenger tests, initiating proposals where necessary to roll-out existing challengers or to implement new challengers.
• Monitor operational drivers of credit risk performance, initiating proposals where necessary to optimise the balance between manual and automated decisioning.
• Develop and maintain the production of regular MI to support the monitoring and evaluation of credit risk KPIs, key drivers and performance of credit risk strategies.
• Develop and maintain the production of credit loss forecasts.
• Identify the need to change; credit strategies, systems functionality, operational processes and data acquisition and deployment (through data analytics and through discussion with colleagues and suppliers).
• Develop proposals, based largely upon data analytics to model the long term value of the change
• Estimating and delivering credit loss assumptions for input into proposals initiated by other areas of the business (e.g., product development proposals, marketing campaign proposals).
• The design and maintenance of data tables in warehouses and marts to maximise their re-use potential across disparate analytics projects, minimising analytics turnaround times and maximising productive capacity.
• Work with internal colleagues and with suppliers to; define requirements, procure, build, test and implement new credit risk capabilities such as new data sources, new scores, new systems and operational processes.

Ideal qualifications, skill sets and experience:

• Strong academic background with a numerical/statistical/science based degree.
• Highly numerate with strong data analysis experience.
• Experience with SAS analytics is essential (SQL, Python, C++ are also acceptable)
• Risk acquisition, capital impairment 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 highly advantageous.

If you have the relevant energy background or career experience skill sets, and would like to know more about the above opportunity, then please apply now.

Due to the amount of applications we receive on a daily basis unfortunately we are only able to respond to the successfully shortlisted candidates. If you have not heard from us within 3-5 days of applying for this position, your application was not successful on this occasion. We may however be able to contact you with a more relevant position at a later date.

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