TIAA Quantitative Asset Modeler in New York, New York
The role involves applying machine learning and quantitative modeling knowledge to maintain and enhance existing asset models, ranging from streamlining processes to development and implementation of empirical analysis to optimizing models at the asset and portfolio level.
Key Duties & Responsibilities:
Support the implementation of the strategy for the modeling of TIAA’s invested assets used in the asset liability projection model that supports actuarial modeling applications
• Develop, maintain, and support the exiting asset models, such as: perform
regular updates and production of model results as required by business
need, implement enhancements to models as directed by Team lead and
• Develop market data adapters for security and reference data for providers like
Reuters, Bloomberg, Intex etc., in order to recalibrate models in a timely
• Integrate third party solutions with in-house systems E.g. GEMS
• Coordinate with other internal teams in Actuarial, IT, Risk Management
understand requirements and automate systems
• Apply econometric techniques to market microstructure data to potentially
improve models and provide feedback to the optimization framework.
NATURE OF IMPACT -
This role supports the implementation of asset modeling capabilities to support the actuarial modeling strategy. The actuarial modeling strategy is being designed and implemented to support current and future modeling applications, including models to project future statutory earnings and balance sheets, to set reserves, to calculate capital requirements, to project future cash flows for ALM analyses, economic capital calculations, etc. Robust asset modeling capabilities are a key component to the modeling strategy and this team provides the expertise and understanding of the modeling of TIAA’s invested assets to ensure model end users have access to timely and accurate model results required to effectively do their job.
AREA OF IMPACT -
This position will support the delivery of asset modeling capabilities under a well-governed framework and the production of model result in a consistent, timely and well controlled manner which will positively impact the work that Actuarial Services can complete and have a beneficial impact to financial performance, decision making and risk management across TIAA.
To apply coding skill and quantitative modeling knowledge to produce results, automate and streamline complex processes and existing code. Highly complex with strong analytical, problem-solving, technical & execution skills.
To apply coding skill and quantitative modeling knowledge in the effort to automate and streamline processes and existing code. High degree of complexity requiring knowledge of advanced coding, statistical modeling techniques and use of statistical modeling packages. Knowledge of capital markets, financial projections or use of stochastic interest rates will be a plus.
Business or Industry Expertise:
Knowledge and understanding of asset classes in which TIAA invests (including fixed income assets, structure securities, real estate, private equity, natural resources and infrastructure) is preferred.
Will interact with members of Actuarial Services, IT, ERM, the Modeling team and Portfolio Management to understand the business, maintain, support and automate systems to enable us to run an effective and robust model operation across Fixed Income, Private Equity, Real Estate, NRI, and other major asset classes.
• BA/BS in Computer Science, Applied Mathematics, data scientist or other
• 1-3 years Coding skills, statistical modeling techniques use of data analysis
tools (R, MATLAB), data analytics
• 3-5 years As above plus experience working with large data sets and building
predictive models to model financial assets.
• Masters in Computer Science, Applied Mathematics
• Experience working with large data sets and building predictive models.
• Advanced programming skills
• Insurance industry experience
Primary Location: NY-New York
Req ID: 1712978