Internship (MFE, Operations Research, Computational Finance, Mathematics
Qontigo, United States
Job Description
SUMMER INTERN - NYC (MFE, Operations Research, Computational Finance, Mathematics)
Does working for a company that embodies innovation, transparency and creativity excite you? Then, we have the place for you.
Bringing together Axioma, DAX and STOXX to form Qontigo represents a partnership beyond standard, creating an investment intelligence advantage with our clients, from risk to return. Qontigo combines the most sophisticated risk analytics and portfolio-construction tools in the market with globally recognized leadership in creating market-defining indices.
We Innovate. We Create. We Collaborate
Responsibilities:
Surrounded by smart passionate colleagues, your main mission will be to contribute to key quantitative development projects within Qontigo’s Research, Quantitative Pricing, and Index Ramp;D teams, including:
- Applying statistical and machine learning methodologies to analyze financial and ESG data sets for use in building models and indices
- Researching, implementing, and testing prototype models to assess portfolio risk and performance
- Investigating factors that drive the performance of financial assets
- Evaluating the impact of portfolio construction choices as part of the index design process
Requirements
- Currently pursuit of an MSc degree (MFE, Mathematics, Operations Research, Computational Finance). Prior Industry experience and understanding of various financial products is a plus.
- Scripting: Python, R or Julia. Experience in C++, C# or Java is a plus.
- Data: Database knowledge, SQL
- Interest in research and development of quantitative finance methodologies and models.
- Interest in projects that could be of the the following types:
- Curve Quality: Improve data quality assessment methods for daily production of spread curves
- Instrument Returns: Develop prototype approaches for computing histories of bond returns for a large standard fixed income universe
- Pricing, Risk, and Data Derivation: Cash dividend model, Heston local stochastic volatility model, surrogate pricing modes in finance, ML for backward stochastic differential equations, Deep Neural Networks for SABR calibration
- Comparing and Analyzing ESG Datasets: Perform statistical analysis, interpret scores, and construct portfolios using scores to understand resulting characteristics
- Developing quantitative sustainable indices, including ESG and climate indices.
- Backtesting of models and ongoing support for Qontigo risk platforms
- Ability to collaborate effectively across teams
- Produce high quality documentation and code related to the project
- Adaptability, innovative thinking, energy, and enthusiasm
- Commitment to building meaningful professional relationships in the financial/technology sector
Benefits
- Lunch amp; Learns with Senior Management
- Mentorship within the Qontigo employee community
- Option to shadow members of various teams across the Qontigo teams
- Collaboration and events with fellow interns