Quantitative Analyst / Data Scientist

Recruiter
LoveWorkLife Limited
Location
Paddington, Greater London
Salary
£60000 - £80000/annum
Posted
13 Jul 2017
Closes
12 Aug 2017
Sector
Accountancy
Contract Type
Permanent
Hours
Full Time
Transformational changes are occurring in UK energy markets which are creating compelling business opportunities. The UK domestic energy market in the UK is large and fast growing (current estimated size of c. £7 billion), driven by developments in solar PV, battery storage, smart meters and other areas.

My client is a start-up consumer credit business. The business has a current loan book of c. £40m.

Job brief
We have very significant ambitions to profoundly change and improve the installation of energy efficient measures in the UK. We are looking for individuals to join us who are hard-working, ambitious and are passionate and enthusiastic about joining a high growth, start-up business.

We are looking for a dynamic quantitative analyst / data scientist to help us with numerous areas of analytics. As a business, data and technology are at the heart of what we do. The role will involve working with the chief risk officer, the chief financial officer and CEO directly, as well as a number of other members of the team who are involved in data analytics. The role will involve the presentation of data analysis in person and in written form. The role will focus on the following, but there is considerable scope for the role to expand into other areas.

Loan book analysis-
We have a current loan book of c. £40m, which has about 12,500 borrowers. Whilst we have completed a significant amount of analysis on this, there is a significant amount of on-going and new analysis to complete on the book in order to understand the book’s performance characteristics, which cohorts are performing better / worse etc.

Credit decisioning-
As a lending business, developing and underwriting credit risk is a key area of focus. We are in the process of developing our credit risk scorecard and would like the data analyst to be very actively involved in the analysis to develop this scorecard based on the performance of the existing book, as well as numerous other data sources which we have access to.

Commercial analysis-
We have access to a significant amount of property data from some of the larger listed online property agents. Access to this data set gives us a deep and wide view of the UK domestic real estate market. This is potentially a very valuable data set for us in that it allows us to; i) generate leads for our installer partners; ii) identify older properties which may benefit from the installation of energy efficient measures, iii) complete customer segmentation of the existing set of borrowers to help our installer partners better target potential customers; iv) identify other trends in the market place

Monitoring return on marketing investment-
Analysis of return on our marketing investment (SEO, PR, other etc) in order to optimise our marketing spend

Monetising the data generated by our installed measures-
Over time, we believe that there could be significant value created in monetising the data generated by some of the energy efficient measures installed in homeowners properties.

Specific Responsibilities
Loan Book Reporting- Weekly and monthly reporting of loan book performance

Sales Reporting- Develop automated tools to develop understanding of sales origination via our installer partners

Analysis of collection of client loans- Ongoing analysis of the structure of the companies loans in order to make the process and flow more efficient

Development of Data Warehouse- We will look to build a data warehouse over the coming 6-9 months, which will be the main repository of information for the business

Specific skills
Specific skills required
• Sequel
• Excel
• VBA

Potentially helpful
• SAS
• R / Python
• Tableau
• Qlikview

Requirements
• 5-8 years of experience in a quantitative role in a commercial setting
• Minimum of MSc or phD in a quantitative subject (maths, economics,
econometrics, physics, computer science, engineering etc)
• History of strong academic performance
• Ability to present data findings clearly and simply

Remuneration
• Attractive remuneration package on offer including equity potential
• Pension and healthcare benefits