Blackstone Multi-Asset Investing – Quantitative Research Analyst

Blackstone is the world’s largest alternative asset manager. We seek to create positive economic impact and long-term value for our investors, the companies we invest in, and the communities in which we work. We do this by using extraordinary people and flexible capital to help companies solve problems. Our $1.1 trillion in assets under management include investment vehicles focused on private equity, real estate, public debt and equity, infrastructure, life sciences, growth equity, opportunistic, non-investment grade credit, real assets and secondary funds, all on a global basis. Further information is available at www.blackstone.com. Follow @blackstone on LinkedIn, X, and Instagram.

Business Group: Blackstone Multi-Asset Investing (BXMA)
 

Business Group Overview:

Blackstone Multi-Asset Investing (BXMA) manages $90 billion across a diversified set of businesses. We strive to generate attractive risk-adjusted returns for our clients across market cycles. Our strategies include Absolute Return, Multi-Strategy, Total Portfolio Management, and Public Real Assets. 

Job Title: Blackstone Multi-Asset Investing (BXMA) – Quantitative Research Analyst

Job Responsibilities:

• Support BXMA’s Quantitative Research team in optimization and risk analytics across BXMA’s businesses.
• Research systematic investment strategies that leverage BXMA’s proprietary data.
• Data Infrastructure: Ongoing development and maintenance of internal data solutions with a focus on highly scalable and computationally efficient data and analytical infrastructure.
• Portfolio Analytics: Develop portfolio analytics across portfolio construction, optimization and risk modeling.
• Quantitative Research: conduct signal research using advanced statistical and machine learning techniques utilizing conventional and alternative data sources, including proprietary BXMA and Blackstone data.
• Collaborate across other BXMA groups, including Investment teams, Operations, Treasury and Legal.
• Perform responsibilities utilizing knowledge and experience applying advanced statistical and machine learning techniques.
• Perform other duties as needed.

Qualifications:

Education:

• Master’s degree (or foreign equivalent) in Finance, Economics, Mathematics, or a related field required.

Experience:

• Minimum 2 years of experience in job offered or related occupations required.
• Minimum 2 years of experience in multi-asset portfolio optimization and/or a related quantitative occupation performing statistical analysis and building mathematical models in the financial industry.
• Minimum 2 years of experience understanding hedge fund strategies and market dynamics, including discretionary macro, systematic equity, CTAs, event-driven equities, and volatility-based strategies, with hands-on experience analyzing market risk exposures and reporting performance attribution.
• Minimum 2 years of experience in a role requiring strong programming proficiency in Python and SQL. with hands-on experience in developing systematic investment engines, data pipelines, and automation frameworks for portfolio construction.
• Minimum 2 years of experience leveraging financial data services and analytics tools, including hands-on experience and proficiency with Bloomberg (BQL/BLP/BQuant), Snowflake, and Tableau for position monitoring, risk assessment, and performance attribution.
• Minimum 2 years of experience sourcing, cleaning, managing, and analyzing large data sets.
• Minimum 2 years of experience applying advanced statistical and machine learning techniques to financial datasets, such as Gaussian Mixture Models for regime classifications, factor-based risk decompositions, and asset volatility time-series analysis.
• Minimum 2 years of experience in financial engineering and mathematical modeling with competency in options, fixed income, linear algebra, probability theory, statistics and machine learning, financial time-series analysis, numerical methods and optimization.
• Experience can be concurrent.

The duties and responsibilities described here are not exhaustive and additional assignments, duties, or responsibilities may be requi