Quantitative Associate

Loomis Sayles is a performance-driven active asset management company that seeks to identify exceptional investment opportunities on behalf of institutional and retail clients worldwide. We believe active management fueled by proprietary, best-in-class research helps us achieve financial success for our clients. Founded in 1926, Loomis Sayles currently oversees approximately $425 billion in assets under management (as of 30 September 2025) for global clients spanning more than 50 countries.

We foster a culture of entrepreneurialism, where all employees are empowered and encouraged to develop themselves and their ideas. Our culture centers on our shared IDEALS, the core characteristics of who we aspire to be as employees and an organization.

INCLUSIVE & DIVERSE-DEDICATED TO TEAMWORK-EXCELLENT-ACCOUNTABLE-LEADERS-SOLUTIONS-ORIENTED

Loomis Sayles is committed to the continual improvement of our performance, processes and people. As part of this commitment, we are looking to hire an enthusiastic and passionate candidate, eager to contribute to our continued success through the following employment opportunity:

About the Role

The Quantitative Associate reports to the Co-Director of the Applied Integrated Quant (Applied IQ) team and assists in providing quantitative support to fundamentally driven investment processes and portfolio management teams within the firm.

In response to the ever-increasing complexity of capital markets and Loomis' investment philosophy to a disciplined investment process, the Applied IQ team has taken the initiative to build quantitative investment tools to support and enhance the firm's fundamental research capabilities and portfolio management capabilities. The position requires knowledge of the various credit (and some equity) strategies managed at the firm, and the underlying investment processes utilized to select stocks/issuers and build portfolios. The Quantitative Associate will act as a key liaison between the Applied IQ team and various fundamental investment product teams, conducting research to support bottom-up and some top-down investment processes in a systematic/quantitative fashion.

The Associate will play a key role in early-stage model development and day-to-day operations, which entails structuring the core components of the quantitative models, building technology infrastructure to facilitate daily production, designing various reporting tools for model risk management and performance attribution.

The position requires both strong quantitative/technical skills and effective written and oral communication skills. Although quantitative in nature, this individual is also expected to have a pragmatic, resourceful and strong problem-solving approach to help solve big picture challenges. The individual will work closely with the Applied IQ team as well as other investment teams across the firm.

About the Team

The Applied IQ team is a stand-alone team within Loomis' Investment Management department that works consultatively and collaboratively with investment teams throughout the firm to provide support and enhance and refine investment processes. The team is based in Boston, MA and is comprised of 9 individuals. Including the Head of Applied IQ, 2 Co-Directors and 6 Quantitative Analysts.

Job Responsibilities

• Partner with investment teams to integrate quantitative tools into their investment processes
• Improve, maintain, run and distribute results of various credit valuation models.
• Contribute to the development of economic regime forecasts, default risk forecasts, risk premium forecast, expected credit returns.
• Contribute to backtesting relative value models.
• Contribute to various research projects in risk modeling
• Work with senior quantitative analysts to support their research efforts
• Follow newly published academic papers and industry trends to explore new product ideas
• Maintain code, database and documentation for relevant production processes
• Practical approach to problem solving and ability to blend quantitative models with fundamental ideas

Qualifications & Education Requirements

• Degree in Computer Science, Data Science, or Engineering. Graduate degree preferred.
• 2+ years of work experience in an analytical capacity
• Hands-on programming skills along with a passion for investing in the financial markets. Proficiency with programming languages and statistical software (e.g., Python, MATLAB, SQL, VBA, Tableau)
• Experience with AI/Machine Learning algorithms and implementation is a plus.
• Demonstrated ability to conduct data analysis - strong Data Science, data visualization skills.
• Excellent communication skills
• Self-driven, highly accountable, resourceful and independent thinker; ability to take initiative to conduct independent research with limited or no guidance.
• Curious and entrepreneurial mindset
• Ability to "think outside the box" and to approach quantitative problems from a unique perspective
• Team orientation and the ability to build widespread credibility with a proactive and open-minded attitude

Loomis Sayles is committed to offering competitive and equitable compensation. The salary range for this position is $70,000 - $100,000 USD. Your starting salary will be based on your experience, skills, qualifications and local benchmarking. This position is also eligible for a discretionary annual incentive award, which is based on individual and company performance. In addition to your compensation, you will have access to a comprehensive benefits package designed to support your health, well-being and financial security.

EEOC and Diversity Statement

Loomis Sayles is deeply committed to building a diverse and inclusive workforce in which talented individuals can realize their full potential and contribute to our growth and success. Please consider applying for this role even if your work history and skillset doesn't completely match the job description. We believe creativity, tenacity and humility are as valuable as specific skills that can be practiced and perfected on the job.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, creed, color, gender, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

---