Quantitative Research Analyst, Systematic Equity, Assistant Vice President, State Street Global Advisors

Quantitative Research Analyst, Systematic Equity, Assistant Vice President, State Street Global Advisors

Company: State Street Global Advisors (SSGA)

Location: London

Who we are looking for

This role is for a Quantitative Research Analyst in the Systematic Equity team. The role is based in London and reports to the Lead Research Supervisor of Systematic Equity.

Systematic Equity team manages a wide range of quantitative equity strategies over a broad active risk spectrum across global markets. The team has a deep history of delivering innovative risk-controlled alpha to our clients and we are looking for someone who can help shape the next phase of our growth with extraordinary analytical skills and passion for data science. You will have an opportunity to combine your analytical skills and investment insights with innovative data and modeling techniques on a cutting-edge distributed computing platform to solve investment problems.

Why this role is important to us

The team you will be joining is a part of State Street Global Advisors, one of the biggest asset managers in the world, that provides services to the world’s governments, institutions and financial advisors across the globe. With over four decades of experience and trillions of dollars in assets under management, we offer one of the broadest selections of services across asset classes, risk profiles, regions and styles. As pioneers in index, ETF, and ESG investing, we are always inventing new ways to invest. Join us if making your mark in the asset management industry from day one is a challenge you are up for.

What you will be responsible for

• Generate ideas for investment process innovation and improvements with key focus in alpha generation and portfolio construction.

• Execute research projects including interpreting, presenting and implementing results.

• Contribute to maintaining and improving our state-of-the-art computing platform for research and production models.

• Explore and evaluate alternative data sources and machine learning techniques to solve investment problems better.

Education & Preferred Qualifications

• Advanced degree (PhD/MS or equivalent) in finance, economics or a quantitative discipline such as computer science, mathematics, statistics, physics or engineering.

• Minimum 2 years of work experience in quantitative finance.

• Deep knowledge of quantitative equity investments.

• Great analytical skills with solid knowledge in statistics.

• Strong problem solving capabilities with attention to details.

• Excellent coding skills with experience in Python, R and/or SQL. Experience with distributed computing is a plus.

• Strong working knowledge of theoretical and practical concepts in machine learning including natural language processing.

• Experience working with a large amount of structured/unstructured data is a plus

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