Quantitative Researcher in GREATER PHILADELPHIA

Background: A prominent Investment Management company dedicated to cultivating an environment of forward thinking is searching for a skilled Quantitative Researcher to join its Artificial Intelligence (AI) Innovation Lab.

The AI Innovation Lab was established as a central hub with a company-wide mission to identify strategic business hurdles and resolve them through the utilization of Artificial Intelligence, Data Science, and optimization techniques. The departments mission is to combine human and machine intelligence to redefine capital markets.

If you possess strategic thinking skills along with expertise in Data Science and Investments, we're eager to hear from you!

What Will You Do:

• utilize Data Science best practices in partnership with portfolio managers, researchers, and traders to improve investment decision-making
• employ the best in AI (machine learning, deep learning, NLP, LLMs) on both structured and unstructured datasets to produce signals for investment opportunities across equities, fixed income, and alternative investments
• utilize your Data Science expertise to enhance alpha generation, boost investment performance, craft trading strategies, and minimize transaction expenses
• harness top tier Artificial Intelligence and Data Science algorithms / tools to refine trading strategies, predict market trends, pinpoint investment opportunities, and fortify decision-making procedures
• encourage a culture of AI innovation in capital markets by staying updated on AI trends and advancements, experimenting with emerging technologies and algorithms, and integrating alternative data sources into model development
• collaborate with Data Engineers and MLOps teams on data transformation, feature engineering, and deploying AI models into production

More Info:

• this is a 100% hands-on role
• full-time HYBRID role located in the Philadelphia Metro Area (onsite + WFH); relocation assistance provided

Responsibilities/Experience:

• must have a Masters or PhD in a highly quantitative discipline (Computer Science, Mathematics, Statistics, Economics, Financial Engineering, etc.)
• must have hands-on applied Data Science experiences within capital markets
• strong theoretical background and practical experience within AI (Machine Learning, Deep Learning, NLP, LLMs, RAGs, Optimization, Statistics)
• hands on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.)
• proficiency building models using Python
• capital markets experience is a MUST

Ping Me: sunil@sudrecruiting.com