Data Scientist (Hybrid - Malvern, PA)

Introduction

The Data Scientist will be part of a high-profile Applied R&D team enabling creative and impactful solutions across Active Equities, Fixed Income, Risk Management, Corporate Finance, and more. The role involves applying deep learning, convex optimization, game theory, stochastic simulation, and other techniques for production solutions in Investment Management.

Responsibilities

• Work on systematically designed research and engineering efforts
• Apply mathematical optimization and applied mathematics skills
• Build machine learning architectures to address specific problem statements
• Utilize Quant standards such as Markowitz and Modern Portfolio Theory, mixed-integer optimization, Black-Litterman, factor models, etc.
• Proficient in Python in development environments like SageMaker, Databricks, etc.
• Create evaluation frameworks with OOS, Sim, and back-test components and analyze results
• Work with Investment Management related data and tasks
• Participate in or complete the CFA or have related financial knowledge
• Read and reproduce research papers in computational settings
• Participate in systematic or quantitative workflows in Investment Management

Requirements

• Significant experience in research settings regarding mathematical optimization and other modeling paradigms
• Experience building machine learning architectures to address specific problem statements
• Comfortable with Quant standards such as Markowitz and Modern Portfolio Theory, mixed-integer optimization, Black-Litterman, factor models, etc.
• Proficient with Python in development environments such as SageMaker, Databricks, etc.
• Experience creating evaluation frameworks with OOS, Sim, and back-test components and analyzing results
• Experience with Investment Management related data and tasks is preferred
• Participation or completion of the CFA or related financial knowledge is valuable
• Ability to read and reproduce research papers in computational settings
• Participation in systematic or quantitative workflows in Investment Management is a plus