Senior Data Management Professional - Financial Engineering - Securitized Products London, GBR ...

Location

London

Business Area

Data

Ref #

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.

The Global Securitized Products Data Team is responsible for researching and supporting a $12 trillion global securitized product market. The securitized product market uses financial engineering to transform a variety of assets (residential and commercial mortgages, auto and equipment leases, managed corporate loan portfolios, credit card debt, and even music royalties) into securities that are structured to meet nearly any investor appetite. Our team supports the full data lifecycle and analytical capabilities, through reverse financial engineering, of all securitized products globally for Bloomberg.

The Securitized Products EMEA CLO & ABS team is responsible for creating and maintaining a large library of cash flow models and data for Public and Private Asset Backed Securities (ABS) including esoterics (Credit Card, Auto, Data Centre, Solar) and Collateralized Loan Obligations (CLOs). The team is responsible for the full stack of work involved in handling these asset sectors, including new issuance and bond data, collateral performance data, cashflow modeling, periodic cashflow and collateral reconciliation, customer support, and client engagement. Our bond data, collateral performance data, and cash flow models are required, along with prepayment and credit assumptions, in order to price these securities accurately and support the expanding markets.

You will play a key role in maintaining and enhancing the team's workflows across the EMEA ABS and CLO product areas. You will partner with clients and external market experts to develop, refine, and validate financial and predictive models, ensuring analytical outputs are robust, scalable, and aligned with client needs.

Leveraging strong expertise in data management and data modelling frameworks, you will contribute to the design and continuous improvement of data quality control frameworks and core data processes. You will help ensure the integrity, consistency and reliability of our analytics and underlying datasets.

Working closely with internal stakeholders across Product and Engineering, as well as directly with clients, you will develop a deep understanding of market workflows and analytical requirements. You will translate these insights into enhancements to our product offering and provide subject matter support on advanced risk analytics and valuations.

In collaboration with Engineering, you will contribute to the design and implementation of financial and predictive models, core analytical calculations, ETL processes, and client facing data and analytics solutions.

• You will build and tie out robust financial and/or predictive models and calculations responsive to all client and market inputs, based on detailed legal financial data and client engagement.
• You will develop testing frameworks and monitors for data and analytical quality controls.
• You will ensure consistency, quality and timely product delivery while providing excellent service to internal and external customers.
• You will partner with Product, Application Specialists and Sales to thoroughly understand our client's workflows to further our model engine, improve our product offering and provide client support for advanced risk analytics and valuations.
• You will research industry standards, trends and best practices on financial analytical calculations, risk analytics and financial and/or predictive models.
• You will understand customer needs and securitized products markets to ensure our dataset and processes are fit for purpose to provide ready to use information.
• You will work in a fast paced, multifaceted and collaborative setting.
• You will assist with the training and mentoring of junior team members.

• 4+ years' relevant experience of professional work experience in Financial Engineering, securitized products or related field.
• Strong analytical abilities with a passion for financial engineering and statistical data analysis.
• Strong aptitude for problem solving, particularly for root cause analysis.
• Strong familiarity with computer programming and data management concepts, including object oriented design, data modelling and algorithms.
• Demonstrated in depth knowledge of relevant financial markets.

• Strong understanding of the securitized products market and Bloomberg terminal functions.
• Strong knowledge of Python, Unix, JIRA.
• Strong CLO subject matter expertise.
• Established relationships with key stakeholders within the European ABS & CLO markets.
• Data design skills for organising data considering both product need, client usability and engineering objectives.
• Excellent written and verbal communication skills, especially when explaining technical processes and solutions to business stakeholders and management.

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, colour, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email