Risk MI Analyst - Energy Markets

Connect Executive Resourcing Limited; Newcastle upon Tyne; On-site; GBP 40,000 - 55,000; Full time

Job summary

A large energy business is seeking an experienced numerical analyst to join their expanding credit risk teams. The role involves extensive data analysis to produce reliable business proposals and risk metrics. Ideal candidates will have a numerical/statistical degree and experience with SAS, SQL, Python, or similar programming languages. Knowledge of credit risk processes is a plus, with strong analytical skills required. This position offers a chance to develop your expertise in credit risk within the UK energy markets.

Qualifications

• Strong academic background with a numerical/statistical/science based degree.
• Highly numerate with strong data analysis experience.
• Experience with SAS, SQL, Python, C++ or R is required.

Responsibilities

• Produce reliable, analytically derived business proposals.
• Develop regular risk metric MI to support credit risk evaluations.
• Understand and select data series from different systems for analysis.

Skills

Data analysis

SAS

SQL

Python

C++

R

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 extensive data analysis.

Programming/modelling experience in SAS is ideal but also Python, SQL, R, C++ are also acceptable.

This is an excellent opportunity for someone with data analysis or risk analyst experience looking to develop their knowledge and skill sets of credit risk processes within the UK energy markets.

(My clients offices are easily commutable via car from Newcastle-Upon-Tyne, Sunderland, Durham, Hartlepool.)

Key responsibilities will include:

• Production of reliable, analytically derived business proposals, to time and quality
• Production of regular reliable risk metric MI.
• The design of analytics samples that yield the most reliable and powerful insights to support business case proposals.
• 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.
• Understanding often obscure and esoteric data and systems issues, selecting and matching data series from across different systems captured at different points in time, with different quality issues, to produce contiguous data sets for reliable analysis and risk metric MI.
• 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 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.
• Analytical experience with either SAS, SQL, Python, C++ or R is required.
• Credit Risk process experience would be ideal but not essential.
• Commercial P&L analysis and statistical model development experience ideal but not essential.
• 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.