Job Title      : Quant C++ 
Experience  : 5-10 Years
Location      : India 

Job Description :

Sample 1:

• A Degree in a Quantitative Field: An undergraduate degree is required. An advanced degree is a plus, but mathematical maturity matters far more than formal qualifications.
• A minimum of 5 years of industry financial modeling experience, including at least 2 years focused on interest rate modeling. Experience in the muni (municipal bonds) space.
• Ability to write robust and efficient code implementing the models. We build analytics using C++; however, expertise in using a different object-oriented language and writing performant code may be sufficient.
• A strong analytical mindset is essential. Whether you hold a PhD in Physics or enjoy reading math books for fun, a keen interest in solving complex analytical problems is crucial.
• Excellent communication skills are required. You will be expected to explain complex concepts to non-technical people in simple, intuitive terms.

Sample 2:

• Quantitative Modeling and Research (QMR) is an innovative team within Single Security Modeling area.
• We specialize in crafting sophisticated risk and valuation models that span a diverse range of products, including interest rates, FX, inflation, equity, and credit.
• Our mission goes beyond traditional quantitative models; we are at the forefront of exploring novel modeling techniques, such as neural networks, to tackle complex problems in quantitative finance.
• Analyze exiting estate of models in rates, FX, inflation, and credit spaces to identify weaknesses that require model revisions.
• Work with the model owners to set up concrete model methodology and implementation plans.
• Work on designing and setting up modeling, testing, and surveillance processes to ensure compliance with the model risk governance policies.
• Review existing model documentation and work with junior team members to bring the documentation to compliance with the model risk governance policies.
• Keep abreast of recent trends in quantitative finance, capital markets and government regulation.

What We Look For

• Advanced degree in quantitative disciplines like mathematics, physics, engineering, or similar.
• Strong practical knowledge of products, modeling methodologies, and analytics in the rates and derivatives space.
• Experience in building valuation and testing platforms and tools in this area.
• Knowledge of model risk governance practices.
• Experience in working with modeling software infrastructure
• Ability to work horizontally across various functions, including portfolio managers and traders, quantitative modelers, model risk governance, RQA.
• 10+ year of industry experience

Sample 3:

• This 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.
• Doing theoretical research to come up with new or find existing models and methodologies in the pricing and risk space, across multiple asset classes including private assets.
• Doing empirical research to calibrate new models to financial data.
• Back-testing, documenting, and guiding new models and methodologies through validation.
• Implementing and maintaining production codebase. Owning the model and managing the use cases in front of stakeholders.
• Additional team 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.

Qualifications:

• Master with 1-3 YOE in Financial Engineering, Mathematics Finance or PhD in Mathematics, Statistics/Econometrics, Science, or other relevant quantitative disciplines.
• Hands-on experience with frequentist and/or Bayesian statistics in time-series analysis. Knowledge of machine learning.
• Knowledge of financial mathematics (derivatives pricing).
• Able to communicate quantitative information and collaborate effectively in a team environment.
• Solid programming skills in Python and a drive and ability to quickly pick up new technologies. Exposure to Git, Unix, or any high-performance computing language is a plus but not required. Exposure to PyTorch/TensorFlow/Jax is a plus but not required
• Exposure to private equity, private credit, Kalman filter/smoother is a plus but not required

Sample 4:

• Lead model governance for Aladdin private markets models including (but not limited to) private equity, private credit, real estate, infrastructure, hedge funds, etc.
• Building and maintaining model governance controls, including (but not limited to) model performance monitoring,
• Model documentation, model remediations and supporting internal & external client model validations
• Communicate (verbally and in writing) with internal stakeholders and external clients on model performance regularly,
• Investigate exceptional model performance, diagnose issues and conduct corrective remediations
• Doing empirical research to calibrate new models to financial data. Back-testing, documenting, and guiding new models and methodologies through validation
• Partner with engineering teams to migrate private markets models onto state-of-art production systems
• 5-8 years of experience in quantitative field / statistical modeling. Experience with portfolio risk analytics, private markets investments, and /or model governance is strongly preferred
• Advanced degree in a quantitative discipline – master’s degree in finance / economics / statistics / financial engineering / math finance, etc.
• Knowledge of investments, portfolio management,  econometrics, and empirical asset pricing
• A strong background in quantitative research
• Hands-on experience with statistical modeling through software (e.g., Python, R, MATLAB) and strong background in programming.  Proficiency with Python is required
• Experience with data handling (ETL, data joining with SQL, cleaning, processing, summarizing, descriptive analysis), and building and back-testing statistical and econometric models
• Experience with any version control system (e.g., git) is strongly preferred
• Prior work experience in financial modeling (e.g., risk models, analytics, private markets)
• Model deployment to production environment is a plus