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Junior Quantitative Analyst

at Credit Benchmark (View all jobs)

London, United Kingdom

Who we are

Credit Benchmark is a financial data analytics company bringing together the credit risk assessments of the world’s leading financial institutions to deliver greater visibility into the credit quality of individual entities.

We are growing rapidly and are looking for a full time Junior Quantitative Analyst to join our London Team.

The role will be based in our London office, with hybrid working.

 

The role

Reporting into the Research team, the ideal candidate will have some experience within in the financial industry with an interest in credit risk and the broader financial markets. We would also consider a recent graduate looking to start their career in finance.

This is a great opportunity to join a collaborative organisation, that builds a unique financial data service harnessing intelligence from some of the most prominent financial institutions around the world. You will also be collaborating with different teams across the company, including the marketing, sales and bank client relationship team. This gives you a unique exposure and insight into numerous departments and areas of the business.

As a Junior Quantitative Analyst, you will be part of a busy and diverse team. You will play a key part in applying your statistical & data analysis knowledge to research & develop new products. You will work with other teams to generate new ideas and implement innovative ways to showcase our data.

As you build your experience and knowledge you will be increasing involved in interactions with existing clients & potential to demonstrate your new products. On the job training and further professional development will be provided allowing for the opportunity to build a comprehensive and valuable skillset.

 

Your responsibilities will include:

  • Finding and fulfilling new ways of using the unique credit risk data, researching, and developing new products
  • Improving and automating internal and external reporting using Python and Sisense
  • Enhancing client-focused data analytics, helping our clients to better understand their credit risk exposure
  • Creating research outputs including white papers, data insights and visualizations
  • Communicating results and recommendations to management
  • Working on research projects, including cooperation with external researchers
  • Engaging with all teams across the company on quantitative analysis and automation projects

 

What we are looking for

Ideally you will have:

  • A Master’s degree or PhD (plus), in a STEM subject or Financial Engineering with a significant statistics component
  • Demonstrable interest and knowledge in financial markets, the economy especially around credit risk
  • Experience in Python (required)
  • Strong data-analytical skills, knowledge of statistics and econometrics
  • The ability to understand technical complexity
  • Proven experience with independent research
  • An intellectually curiosity, with the drive and ability to demonstrate initiative to improve existing processes
  • Strong attention to detail whilst being diligent and determined to deliver high-quality output
  • Excellent administrative and project management skills
  • Experience in managing competing priorities and effectively deliver to deadlines
  • Excellent communication skills, both oral and written

Let us know if you also have:

  • Experience using any of the following:
  • SQL
  • R

 

Benefits:

  • Hybrid and flexible working hours: Healthy work/life balance
  • Holidays: Competitive holiday package
  • Health and Wellbeing: Private health Insurance cover and paid sick and bereavement leave Pension: Opportunity to join company pension plan with financial education and support
  • Travel: Cycle to work scheme
  • Family Friendly: Supportive environment and paid leave for new parents
  • Learning and Development: Professional development opportunities through seminars, conferences, training and courses and internal mentorship
  • Community: Supportive, collaborative, and social team environment

 

Our commitment to diversity, equity, and inclusion

At Credit Benchmark, we are deeply committed to diversity, equity and inclusion. This means celebrating who we are as individuals and as a team because our company and culture reflect the sum of our employees.

We strive to create a mindful and respectful environment that includes fairness, kindness, and understanding. We empower each other to bring our authentic selves to work and champion our colleagues’ development and achievements. Our diversity brings a multitude of perspectives and ideas and is imperative to the success of our business.

We are dedicated to ensuring that principles of diversity, equity and inclusion are rooted in Credit Benchmark’s DNA. We continue to build on these principles as our company grows while retaining the progress we have made as team.

Credit Benchmark is proud to be an Equal Employment Opportunity employer. We believe no one should be at a professional disadvantage because of their background. We do not discriminate based upon any legally protected characteristic and are committed to fostering a working culture that is free of discrimination and harassment.

Credit Benchmark is also committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures and employment.

If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please let us know by contacting our HR team at [email protected]

 

Only successful candidates will be contacted.

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    Credit Benchmark brings together internal credit risk views from over 40 leading global financial institutions. The contributions are anonymized, aggregated, and published in the form of consensus ratings and aggregate analytics to provide an independent, real-world perspective of credit risk. Risk and investment professionals at banks, insurance companies, asset managers and other financial firms use the data for insights into the unrated, monitoring and alerting within their portfolios, benchmarking, assessing and analyzing trends, and fulfilling regulatory requirements and capital.