EconJobMarket®

Advertiser: BlackRock

Field(s) of specialization: Finance - Other

Position type(s): Other nonacademic

Location of job: United States

Degree required: Doctorate

Job start date: Flexible

Job duration: Continuing/permanent

Application deadline: 31 Jan 2022 midnight UTC (no longer accepting applications)

Current search status: Reviewing applications

Posting end date: 31 Jan 2022

Interviews: Interviews will be conducted remotely by video starting January, 2022.

Ad text:

Job Description

Elevate your career by joining the world's largest asset manager! Thrive in an environment that fosters positive relationships and recognizes outstanding performance! We know you want to feel valued every single day and be recognized for your contribution. At BlackRock, we strive to empower our employees and effectively engage your involvement in our success.

Business Unit Overview:

Come join a diverse and collaborative team of researchers at the Financial Modeling Group (FMG) who are responsible for the research and development of financial models underpinning the risk management and relative value analytics produced at BlackRock. The group also contributes to the infrastructure platform to produce analytics and the delivery of analytic content to portfolio and risk management professionals both within and outside BlackRock. Given the diversity of business objectives among BlackRock Solutions clients and within BlackRock itself the models developed and supported by the Financial Modeling Group span a wide array of financial products, ranging from equity to fixed income to derivatives. In addition, members of FMG seek to provide analysis and insight on many different levels from analysis of the cash flows of a single bond to the overall financial risk associated with an entire portfolio, enterprise, or balance sheet.

The position will be based onsite in our New York office.

Key Responsibilities:

The Economic Scenario Simulation team specifically is building out a new engine for the joint simulation of the global macro economy, drivers of financial markets, and individual assets. The team is building and connecting innovative models and methodologies across these spaces in a Bayesian framework. The engine is used in scenario analysis and portfolio construction / strategic asset allocation.

Examples of current projects are:

• Develop non-linear filtering and estimation techniques for state space models with stochastic volatility and correlation.
• Design an integrated rating migration model that simultaneously describes real world rating migrations and spread curve movements.
• Develop a term-structure model that works with works well with unconventional monetary policy and lo
• Fit a macroeconomic model to various sources of data such as historical observations, forecasts, and expert knowledge about impulse response functions.

Responsibilities include

• Doing theoretical research to come up with new or find existing models and methodologies in the risk space, across multiple asset classes.
• Doing empirical research to calibrate new models to financial data.
• Backtesting, documenting, and guiding new models and methodologies through validation.
• Communicate with internal and external clients to identify industry-wide quantitative problems and collaborate with academics affiliated with BlackRock to explore solutions.
• Collaborate on papers for publication, presenting original research at industry conferences, and speaking with institutional clients about relevant research.

Additional job responsibilities may include working with portfolio management teams on bespoke projects supporting their investment processes or working with financial advisory teams on modeling projects for bespoke products.

Skills & Qualifications

• PhD in Finance, Statistics/Econometrics, Economics, or other relevant quantitative disciplines.
• Hands-on experience with frequentist and/or Bayesian statistics in time-series analysis, and/or basic machine learning techniques. Prior experience with state space models is a plus.
• Demonstrated ability to conduct high quality empirical research or theoretical research relevant for empirical analysis.
• Able to communicate quantitative information and collaborate effectively in a team environment.
• Solid programming skills in Python, R or Matlab and a drive and ability to quickly pick up new technologies. Exposure to Git, Unix, SQL, or any high-performance computing language is a plus but not required.