Bloomberg
Senior Data Analyst - Securitized Products Collateral Assets Data
Bloomberg, Skillman, NJ
Description & Requirements
Our Team:
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 Assets Team focuses on extracting, normalizing, and loading collateral data to the Bloomberg Terminal. To do so, the team uses Python to navigate complex ETL workflows to ensure that data across various sectors is modeled and managed properly within our loans database. This database drives collateral information for data license, enterprise data, and the screens on the Bloomberg terminal which gives clients access to granular information that allows them to make empowered investment decisions. The team works closely with all of our other Securitized Products teams as well as our Engineering and Business Product counterparts.
What's the Role?
You will be responsible for both creating and maintaining sustainable extraction, transformation, and loading processes for raw collateral data onto our system for sectors such as Collateralized Loan Obligations (CLO), Residential Mortgage-Backed Securities (RMBS), Commercial Mortgage-Backed Securities (CMBS), and various Asset Backed Securities (ABS, Credit Card, Auto, SLABS). You will need to leverage python skills to initiate the ETL processes in conjunction with loan amortization knowledge to properly derive and calculate various data points regarding collections. You will also monitor monthly collateral payment updates and evaluate deals with loans outside of specified thresholds to ensure quality is within our client's expectations, as well as troubleshooting any ETL failures and implementing the appropriate code changes.
You will also have the opportunity to participate in larger coverage expansion initiatives for previously unsupported loan types. This involves performing necessary market and analytical research to ensure proper functionality from both a workflow and data ingestion standpoint, as well as working closely with engineering and business to implement. There are also opportunities to analyze bulk collateral data sets for various clean-up efforts and implement solutions to clean that data both historically and sustainably moving forward.
We'll trust you to:
You'll need to have:
We'd love to see:
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are!
Salary Range = 85000 - 105000 USD Annually + Benefits
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation, [Exempt roles only], paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Our Team:
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 Assets Team focuses on extracting, normalizing, and loading collateral data to the Bloomberg Terminal. To do so, the team uses Python to navigate complex ETL workflows to ensure that data across various sectors is modeled and managed properly within our loans database. This database drives collateral information for data license, enterprise data, and the screens on the Bloomberg terminal which gives clients access to granular information that allows them to make empowered investment decisions. The team works closely with all of our other Securitized Products teams as well as our Engineering and Business Product counterparts.
What's the Role?
You will be responsible for both creating and maintaining sustainable extraction, transformation, and loading processes for raw collateral data onto our system for sectors such as Collateralized Loan Obligations (CLO), Residential Mortgage-Backed Securities (RMBS), Commercial Mortgage-Backed Securities (CMBS), and various Asset Backed Securities (ABS, Credit Card, Auto, SLABS). You will need to leverage python skills to initiate the ETL processes in conjunction with loan amortization knowledge to properly derive and calculate various data points regarding collections. You will also monitor monthly collateral payment updates and evaluate deals with loans outside of specified thresholds to ensure quality is within our client's expectations, as well as troubleshooting any ETL failures and implementing the appropriate code changes.
You will also have the opportunity to participate in larger coverage expansion initiatives for previously unsupported loan types. This involves performing necessary market and analytical research to ensure proper functionality from both a workflow and data ingestion standpoint, as well as working closely with engineering and business to implement. There are also opportunities to analyze bulk collateral data sets for various clean-up efforts and implement solutions to clean that data both historically and sustainably moving forward.
We'll trust you to:
- Analyze our loan database extraction processes to find opportunities for efficiencies and providing increased value to external and internal clients
- Ensure a high degree of data quality as you maintain, build, and enhance our ETL process
- Evaluate monthly quality test failures for deals with loans outside of specified thresholds
- Debugging collateral extraction failures on a monthly basis
- Onboarding collateral datasets for Securitized Product deals at issuance on a daily basis
- Analyze internal processes to identify potential opportunities for improvement
- Understand customer needs and Securitized Products markets to ensure our collateral datasets and processes are fit-for-purpose to provide ready to use information
- Communicate and collaborate across teams both within Securitized Products and with our various partners in Engineering, Data, and Product
You'll need to have:
- Bachelor's degree in Finance, Business, Economics, Accounting, STEM or related degree/equivalent experience
- 4+ years of relevant work experience
- Legal authorization to work in the US without visa sponsorship now and in the future
- Working proficiency with Microsoft Excel and comfortable with command line tools
- Familiarity with reading and writing code (Python preferred)
- Project management skills and the ability to multitask in a fast-paced environment
- Ability to work independently as well as collaboratively in a team environment
- Ability to adapt to changing priorities and product needs
We'd love to see:
- Knowledge or experience in Securitized Products
- Knowledge of collateral amortization or collateral underwriting in a Securitized Product sector
- Experience working in GitHub and submitting pull requests
- Understanding of Data Management and Data Analysis best practices
- Experience working in an Agile/Scrum environment
- Willingness to train and mentor others
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are!
Salary Range = 85000 - 105000 USD Annually + Benefits
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation, [Exempt roles only], paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.