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Posted 8/31/20

Quantitative Analyst,
Voya Financial

For full information and to apply, visit this link.

Voya Investment Management (Voya IM) is the asset management business of Voya Financial, a Fortune 500 company with over 6,000 employees seeking to help clients plan, invest and protect their savings. Voya IM manages approximately $214 billion in assets across Fixed Income, Senior Loans, Equities, Multi-Asset Strategies & Solutions, Private Equity, and Real Assets. Drawing on over 40 years of experience and the expertise of 250+ investment professionals, Voya IM’s capabilities span traditional products and solutions as well as those that cannot be easily replicated by an index.

Voya’s quantitative equity research team develops factor-driven stock selection models for systematic investment strategies and in support of the fundamental platform. The team is directly and indirectly responsible for a combined total of approximately $31 billion in AUM (as of 6/30/2020).

Key Responsibilities
The analyst will work within a team of quantitative researchers and portfolio managers to assist in developing, implementing, and enhancing quantitative models and analytics used to support the Equities platform at Voya Investment Management. 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 so as to systematically identify alpha opportunities in different segments of the equity market. Research areas include identifying new alpha factors, model estimation (linear and nonlinear), portfolio construction, and risk management. The analyst will be expected to contribute to the shared codebase and toolkit of the research team.  Combining newly available data with innovations in machine learning is key to capturing fundamental investment intuition and insights from behavioral finance in more nuanced and effective ways. This role offers a unique opportunity for the right candidate to gain in-depth understanding of “quantamental” investing and hands-on experience with the latest data science techniques applied thereto.

Responsibilities include:
• Work on innovative research projects aimed at advancing our proprietary multi-factor models through the addition of new alpha signals or better model estimation techniques, both linear and nonlinear.
• Explore enhancements to portfolio optimization and risk management to improve the risk-adjusted net returns of our systematic investment strategies or target specific investment outcomes for our clients.
• Evaluate new data sources from a range of sources for their potential to generate alpha.
• Help maintain and advance the team’s shared codebase, data repositories, and cloud-based technology stack.
• Contribute to new product development in collaboration with our client-facing and product teams.
• Contribute to thought leadership articles to enhance awareness of our team’s investment philosophy and capabilities.

Qualifications
• Bachelor’s degree in a quantitative discipline such as Financial Engineering, Operations Research, Mathematics, Computer Science, Statistics, etc. Advanced degree preferred. CFA a plus.
• 5 years of relevant work experience in applied quantitative research, preferably investment management.
• Strong analytical and mathematical skills. Excellent working knowledge of econometrics and statistics. Familiarity with financial statement analysis is a plus.
• An understanding of a variety of machine learning techniques (clustering, decision tree learning, boosting & stacking, artificial neural networks, etc.), their practical advantages and short-comings, as well as approaches to make the resultant models interpretable.
• Hands-on experience across broad range of modern analytic and data tools, particularly Python; numpy/pandas; machine learning packages such as XGBoost, PyTorch, TensorFlow, Keras; and distributed data/computing tools such as Hadoop, Spark, and SQL. Solid understanding of relational and non-relational databases.
• Experience using one of the Big 3 cloud-based computing services (Azure, AWS, Google Cloud) is a plus.
• Experience with financial databases such as Compustat, Worldscope, Factset, Clarifi/CapitalIQ, Axioma, Barra, Bloomberg is a plus.
• Experience in factor-based equity investing including ESG metrics is a plus.
• 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.