Quantitative Execution Researcher

Stifel•New York, NY

6d•$150,000 - $250,000

About The Position

The Quantitative Execution Researcher works closely with the Electronic Trading team under the direction of the Senior Quantitative Researcher in the development, assessment and management of equity execution models, transaction cost models, and order routing strategies. The responsibilities of this position include initiating research into execution signals and model factors. The Quantitative Research team works closely with the development team to determine which research projects are suitable for further analysis or deployment into Stifel execution algorithms.

Requirements

Strong team player with demonstrated interest in equity trading.
Ability to use quantitative and data science techniques to research and develop appropriate models and tools for use by trading algorithms.
Ability to understand which quantitative research is commercially viable and computationally efficient.
Strong knowledge of programming skillset, Python, SQL, and kdb+/q.
Familiarity with US equities market structure.
Creativity/ability to adapt to and define process.
Detail oriented, self-motivated, independent and a strong communicator.
Graduate Degree in computational finance / financial engineering
1+ year related experience in US equity quantitative research/trading at a financial services firm.

Nice To Haves

Knowledge of time-series data platforms (q/KDB+, etc.)

Responsibilities

Develop strong knowledge of Stifel’s Electronic Trading business and development process.
Apply computational, mathematical, and statistical techniques in support of equity execution algorithm development, transaction cost modeling, and performance analysis.
Originate quantitative models and analytical tools to address issues such as short-term volume/price forecasting, sentiment analysis, signaling, execution optimization, performance measurement, and risk attribution.
Maintain existing quantitative processes and develop new core analytical capabilities or model libraries, using advanced statistical, machine learning and quantitative techniques.
Devise or apply independent models or tools to help verify results of analytical systems.
Interpret results of analytical procedures and recommend new processes and or action plans.
Work closely with trading, technology, and model validation teams to document and improve product offering.
Present research findings/insights to team members.