- Financial Quantitative Analysts should be able to assess conceptual foundations of a model, model specification, underlying assumptions, limitations, variable selection, underlying data, developmental evidence, documentation
- Create, implement, and support quantitative models for the trading business leveraging a wide variety of mathematical and computer science methods and tools including hardware acceleration
- Develop (derivative) pricing models using mathematical finance for valuation including Monte Carlo Methods and partial differential equation solvers
- Develop Forecasting models using Statistical or ML methods, time-series information
- Forecast company-specific announcements – earnings, dividends, or other key ratios
- Forecast collateral-specific information – prepayment rates, default rates, impairments, write-offs, etc.
- Forecast prices, returns, use to calculate optimally
- Meet with company officials to gain better insight into the company’s prospects and management, and with investors to explain recommendations
- Develop quantitative financial products used to inform individuals or financial institutions engaged in saving, lending, investing, borrowing, or managing risk
- Investigate methods for financial analysis to create mathematical models used to develop improved analytical tools or advanced financial investment instruments
- Define or recommend model specifications or data collection methods
- Create or apply independent models or tools to help verify results of analytical systems
- Write requirements documentation for use by software developers. Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope
- Identify, track, or maintain metrics for trading system operations
- Research new products or analytics to determine their usefulness. Provide application or analytical support to researchers or traders on issues such as valuations or data
- Develop core analytical capabilities or model libraries, using advanced statistical or quantitative techniques
- Research or develop analytical tools to address issues such as portfolio construction or optimization, performance measurement, attribution, profit and loss measurement, or pricing models
- Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation
Preferred Education
- Bachelor, Master or Ph.D. degree in STEM, mathematics, finance, computer science, or computer engineering; or finance, or MSc in Financial engineering
Required Skills
- 3+ years of experience in comparable quantitative modeling or analytics role, ideally in the financial sector
- Excellent mathematical and modeling skills
- Broad statistical toolkit including machine learning, econometrics, and non-parametric methods, Experience with statistical techniques in empirical finance
- Proficiency in C++ including STL, C#, .NET, Java, Python, object-oriented software design, Structured Query Language (SQL), or NoSQL such as Time-series DBs including kdb+, document databases like MongoDB, graph DBs, etc.
- Stochastic Calculus, Mathematical finance/ programming, and Probability or Statistics/Econometrics/Machine Learning
- Experience with factor modeling and portfolio optimization
- Strong programming skills in languages such as Matlab, Python, C++, and C#
- A problem-solver, adept at dealing with quantitative-based problems
- Familiarity with Agile methodologies
- Excellent written and verbal English communication skills
Preferred Skills
- Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
- Knowledge of predictive modeling, statistical sampling, optimization, machine learning, and artificial intelligence techniques
- Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
- Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
- Experience with data analytics tools (e.g., Alteryx, Tableau, MATLAB)
