Society of Exploration Geophysicists
Principal Applied Scientist
Society of Exploration Geophysicists, New York, New York, us, 10261
Principal Applied ScientistRole:We are seeking a highly skilled Principal Applied Scientist to join a leading quantitative investment team. The successful candidate will play a pivotal role in developing and applying advanced machine learning and statistical models to drive alpha generation, including the application of cutting-edge LLMs and Generative AI concepts.Responsibilities:Research and Development:
Conduct groundbreaking research in machine learning, statistical modeling, and other quantitative techniques to identify new investment opportunities.Model Development:
Develop and implement sophisticated models for portfolio construction, risk management, and market forecasting.Data Analysis:
Analyze large datasets to extract meaningful insights and inform investment decisions.Collaboration:
Work closely with investment professionals, portfolio managers, and other team members to translate research findings into actionable strategies.Innovation:
Stay abreast of the latest advancements in quantitative finance and technology, driving innovation within the firm.Qualifications:PhD in a quantitative field such as statistics, mathematics, computer science, or a related discipline.Strong programming skills in Python, R, or other relevant languages.Deep understanding of LLMs, machine learning algorithms, statistical modeling, and time series analysis.Proven track record of research and publication in top-tier journals or conferences.Excellent problem-solving and analytical skills.Ability to work independently and as part of a team.
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Conduct groundbreaking research in machine learning, statistical modeling, and other quantitative techniques to identify new investment opportunities.Model Development:
Develop and implement sophisticated models for portfolio construction, risk management, and market forecasting.Data Analysis:
Analyze large datasets to extract meaningful insights and inform investment decisions.Collaboration:
Work closely with investment professionals, portfolio managers, and other team members to translate research findings into actionable strategies.Innovation:
Stay abreast of the latest advancements in quantitative finance and technology, driving innovation within the firm.Qualifications:PhD in a quantitative field such as statistics, mathematics, computer science, or a related discipline.Strong programming skills in Python, R, or other relevant languages.Deep understanding of LLMs, machine learning algorithms, statistical modeling, and time series analysis.Proven track record of research and publication in top-tier journals or conferences.Excellent problem-solving and analytical skills.Ability to work independently and as part of a team.
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