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Voya Investment Management is seeking a Quantitative Research Analyst for its Systematic Equities team. You will support data, research, and production infrastructure that underpins the systemic investment process.
The role sits at the intersection of data science and investment analysis, working with researchers and PMs to identify alpha opportunities. You will build data pipelines, maintain codebases, and explore new data sources.
Together we fight for everyone's opportunity for a better financial future.
We will do this together - with customers, partners and colleagues. We will fight for others, not against: We will stand up for and champion everyone's access to opportunities. The status quo is not good enough ... we believe every individual and every community deserves access to financial opportunities. We are determined to support both individuals and communities in reaching a better financial future. We know that reaching this future depends on our actions today.
Like our Purpose Statement, Voya believes in being bold and committed to action. We are committed to a work environment where the differences that we are born with - and those we acquire throughout our lives - are understood, valued and intentionally pursued. We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work. Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision.
Are you ready to join a company with a strong purpose and a winning culture?
The Quantitative Research Analyst will join Voya Investment Management's Systematic Equities team, which manages approximately $23b in systematic and index assets and supports a broader equities platform. The Analyst will work within a team of quantitative researchers, machine learning engineers, and portfolio managers to support the data, research, and production infrastructure underlying our systematic investment process. Our team sits at the intersection of data science and investment analysis, working closely with fundamental sector analysts for cross-fertilization of ideas. We develop investment insights through exploring datasets and analytical methods to systematically identify alpha opportunities in different segments of the equity market. Research areas for the team include identifying new alpha factors, model estimation (linear and nonlinear), portfolio construction, and risk management.
The Quantitative Research Analyst role is primarily focused on data engineering, quantitative infrastructure, model implementation and production support. They will be expected to help maintain and contribute to the shared codebase and toolkit of the research team. As a part of the Systematic Team, the Analyst will be given plentiful opportunities to participate in alpha generating research and the portfolio management process.
Degree in a quantitative discipline such as Financial Engineering, Operations Research, Mathematics, Computer Science, Statistics, etc. Working towards a CFA a plus.
0-5 years of relevant work experience in applied quantitative research, preferably investment management. Strong recent graduates are encouraged to apply.
Strong analytical and mathematical skills. Excellent working knowledge of econometrics and statistics. Familiarity with financial statement analysis is a plus.
Hands-on experience across broad range of modern analytic and data tools, particularly Python (numpy/pandas, machine learning packages such as XGBoost and SKLearn) with a solid understanding of relational databases.
Bonus points for experience with cloud services (eg Azure), financial datasets (eg factset, bloomberg), and factor investing.
Attention to detail, curious, and self-motivated. Ability to work independently and collaboratively within the broader research team, as well as prioritize tasks.
Excellent problem solving, interpersonal and communication skills. Ability to translate quantitative insights into actionable process improvements
Have a passion for data science and financial markets, the curiosity to master new technologies and techniques, and a desire to drive transformational change.
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