Financial Data Science Associate - KTP Associate with Funds-Axis

Job Description & Qualification

Job Purpose:
To develop a robust, cloud-based, scalable Value-at-Risk and Risk Analytics solution for retail risk investment funds.

Main Activities and Responsibilities:
Queen’s University Belfast in partnership with Funds-Axis have an exciting employment opportunity for a postgraduate to work on a project to develop a robust, cloud-based, scalable Value-at-Risk and Risk Analytics solution for retail risk investment funds.
Funds-Axis is a leading provider of investment compliance monitoring, risk and regulatory reporting solutions to the global investment management industry. They offer a unique combination of highly efficient and secure, multi-modular technology coupled with the highest levels of expert regulatory support and service, delivered through a single application, multi-modular cloud based technology, 'Highwire'.
This is an outstanding opportunity for a talented and self-motivated postgraduate to work in Funds-Axis (located in Belfast) on a 24 month collaborative project with academics from the Management School at Queen’s.
The KTP Associate will lead on the delivery of the following key project stages under the guidance of company and academic
supervisors:
1. Theoretical approach determination of Value at Risk (VaR) prediction engine.
2. VaR model building.
3. Scenario analysis and stress testing.
4. Model evaluations.
5. Analytics platform deployment.

Essential Criteria:
Please note that the Shortlisting Panel cannot make assumptions on your experience or qualifications; it is the responsibility of the applicant to evidence their suitability for the role. As such your Application Form, CV and/or Cover Letter must clearly demonstrate how your Qualifications and Experience meet the Essential Criteria and, where possible, Desirable Criteria as listed in the Candidate Information Booklet. Please ensure that you address all the criteria in the person specification and provide evidence to support your statements.
1. Hold, or be about to obtain (within the next six months), a PhD degree in a relevant field, such as Quantitative/Computational Finance, Econometrics, Quantitative Economics, Applied Statistics or Computer Science. Candidates must clearly state their qualifications and grades, expected date of completion when making their application.
2. Knowledge of market risk.
3. Demonstrable experience in advanced statistical analysis and computer age statistical inference* (*may be demonstrated through the completion of a student project or placement).
4. Relevant experience in the area of machine learning and AI* (*may be demonstrated through the completion of a student project or placement).
5. Demonstrable proficiency in a relevant programming language, such as R, Python or equivalent* (*may be demonstrated through the completion of a student project or placement).
6. Demonstrable experience of managing a significant data analytics project over its life-cycle* (*may be demonstrated through the completion of a student project or placement).
7. Demonstrable ability to run complex models and extract economic meaning* (*may be demonstrated through the completion of a student project or placement).
8. Demonstrable proficiency with common data science and machine learning libraries and packages* (*may be demonstrated through the completion of a student project or placement).
9. Good oral, written and presentation skills.
10. High level of IT skills.
11. Ability to think logically, create solutions and make informed decisions.
12. A high level of numeracy and the ability to interpret data.
13. The ability to think critically about a statistical problem using real data.
14. Self-motivated, capable of working independently, with a drive and ambition to suceed.
15. Ability to work effectively as a member of a group.
16. Enthusiam for research/project area.
17. Well organised, attention to detail and ability to meet tight deadlines.
18. An interest in staying with the Company. (Associates are normally invited to apply for permanent positions).
19. Ability to take part in Associate management courses (requiring two one-week periods in England).
20. Willing/able to travel throughout the UK and Ireland and abroad, as necessary.

Desirable Criteria:
1. Relevant work experience.
2. Knowledge of VaR risk analytics.
3. Proficiency with one or more relevant common GUI data science tools.
4. Experience of AWS or other cloud based technologies.
5. Proficiency with data visualisation tools or libraries
6. Ability to deliver training and follow-up support to operatives.
7. Ability to influence people effectively.
8. Tenacious and committed to achieving goals.

Please note the start date for this role is flexible.

Application Procedure

Please apply via the Queen's University Belfast Careers page: https://bit.ly/3s1vwCk

Closing date: 13th January 2022

About the Organization

The KTP Programme has been helping businesses throughout the UK for over 40 years by recruiting suitably qualified graduates to deliver strategic innovation projects in industry. A KTP role is the perfect launchpad, helping accelerate your career by giving you the opportunity to apply your academic knowledge and skills to a real-life challenge that delivers tactical change within a company. One of the unique benefits to KTP is that you will have access to a substantial training and development budget, and have the support and guidance of Queen’s world class academics and researchers. Queen’s University Belfast is one of the leading universities in the UK and Ireland, with a distinguished heritage and history. As a member of the Russell Group of UK research-intensive universities, Queen’s University Belfast combines excellence in research and education with a student centred ethos. As a leader of Knowledge Transfer Partnership (KTP) development and delivery for 25 years, KTP is held in high regard within Queen’s and the programme has been the foundation for many research and teaching successes including 19 National KTP Awards.

Additional Information

Please note the start date for this role is flexible.

Salary: £34,000 - £42,000 per annum. Plus One of the key KTP benefits for graduates is access to a £6,000 training and travel budget over the 24-month project.

Anticipated Interview Date: Wednesday 26 January 2022

For Additional Questions

k.mcgeough@qub.ac.uk

Job ID

ID: J10181