Quantitative Research, Associate

BlackRock•San Francisco, NY

1d•Hybrid

About The Position

About this role BlackRock is one of the world’s preeminent asset management firms and a premier provider of global investment management, risk management and advisory services to institutional, intermediary, and individual investors around the world. BlackRock’s mission is to create a better financial future for our clients. We have a responsibility to be the voice of the investor, and we represent each client fairly and equally. Constant communication with a diverse team of partners strengthens us and delivers better results for our clients. Continuous innovation helps us bring the best of BlackRock to our clients. BlackRock offers a range of solutions — from rigorous fundamental and quantitative active management approaches aimed at maximizing outperformance to highly efficient indexing strategies designed to gain broad exposure to the world’s capital markets. Our clients can access our investment solutions through a variety of product structures, including individual and institutional separate accounts, mutual funds and other pooled investment vehicles, and the industry-leading iShares® ETFs. Systematic Active Equity (SAE) is the quantitative equity group within BlackRock. We invest our client assets using a systematic investment approach. SAE is a pioneer and thought leader in the industry and has consistently achieved client investment goals across global equity markets for over 30 years. We believe research and innovation is critical to continuing our success and believe in a multi-disciplinary approach that intersects traditional finance and economics with computer and data science. We are seeking a Quantitative Researcher to complement our investment team. The successful candidate is passionately interested in investing, and researching ideas and testing them on historical data to seeing which specific stocks and broad-based factors a portfolio buys and sells resulting from those ideas. This candidate also approaches new data and research ideas with an open mind and a strong belief in the scientific research process. We are considering candidates at all levels of experience. We have: $100+ billion USD under management, including $5+ billion in hedge funds A team of world class researchers, portfolio managers, and data scientists Through BlackRock, access to some of the best investors and thought leaders, as well as leading experts in statistics, machine learning and optimization A 40-year plus track record of performance innovation - from early quant pioneering in the 1980s to the cutting edge of data-driven investing today You have: A passion for data and a keen attention to detail A desire to research and develop investment ideas and strategies, and to onboard and manage data in an effective way Boundless creativity and a desire to constantly learn The desire to work in a team environment with quantitative investors of many different backgrounds You should also have: 2+ years of work experience in the financial domain A Bachelors, Masters, or PhD in a quantitative discipline: e.g., economics, finance, statistics, applied mathematics, computer science Experience working with data and/or conducting empirical research utilizing large, complex data sets Financial market experience: asset pricing, portfolio optimization, macroeconomics, global stock selection, or a similar relevant field Familiarity with natural language processing, machine learning, and/or artificial intelligence. Strong programming skills, either from a data pipeline background (AWS, Hadoop, Spark, SQL), and/or statistical analysis background (Python, R, Matlab, ML libraries)

Requirements

2+ years of work experience in the financial domain
A Bachelors, Masters, or PhD in a quantitative discipline: e.g., economics, finance, statistics, applied mathematics, computer science
Experience working with data and/or conducting empirical research utilizing large, complex data sets
Financial market experience: asset pricing, portfolio optimization, macroeconomics, global stock selection, or a similar relevant field
Familiarity with natural language processing, machine learning, and/or artificial intelligence.
Strong programming skills, either from a data pipeline background (AWS, Hadoop, Spark, SQL), and/or statistical analysis background (Python, R, Matlab, ML libraries)