Data Scientist (Quantitative Researcher)
Background : A publicly listed Global Alternative Investments company, specializing in tailored investment and advisory services, is actively looking to recruit a Data Scientist for its Advanced Quantitative team.
What Will You Do :
- leverage Data Science best practices collaboratively with portfolio managers and fundamental researchers to enhance the performance of client alternative investment portfolios
- utilize machine learning techniques on proprietary and public data for various purposes including constructing portfolios, forecasting client liquidity, and refining cash flow modeling
- develop predictive models illustrating the impact on portfolio performance due to changes in asset allocation and exposure to prevailing market conditions
- utilize NLP, LLMs, RAG models for information retrieval and to generate AI driven responses to client inquiries
- build innovative analytical solutions, such as predictive models forecasting market trends, pinpoint investment opportunities, and delivering valuable insights to clients
- take an active role in the development, testing, and deployment of predictive models
- demonstrate proficiency in Statistics, effectively convey optimal modeling techniques to align with business objectives, exhibit critical thinking skills in articulating model assumptions and complexities, and proficiently communicate model outputs and results
- promote an environment of AI innovation by staying abreast of AI trends and advancements, experimenting with emerging technologies and algorithms, and incorporating alternative data sources into the development of models
More Info :
- this is a 100% hands-on Data Scientist role
- full-time HYBRID role located in the San Diego Metro Area (onsite + WFH); relocation assistance provided for those that require it
Responsibilities / Experience :
- must have a Masters or PhD in a highly quantitative discipline (Computer Science, Mathematics, Statistics, Economics, Financial Engineering, etc.)
- must have 2+ years of hands-on applied Data Science experiences within Finance
- strong theoretical background and practical experience within Data Science (Machine Learning, Linear Regression, Logistic Regression, Optimization, Statistics)
- proficiency building models using Python or R
Ping Me : [email protected]
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