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Quantitative Researcher Machine Learning Jobs in Peabody, MA

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

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Quantitative Researcher Machine Learning information

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$58.3K

$132.3K

$218.1K

How much do quantitative researcher machine learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for quantitative researcher machine learning in Peabody, MA is $132,273.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,100.00 and $169,300.00 per year, depending on experience, location, and employer.

What cities near Peabody, MA are hiring for Quantitative Researcher Machine Learning jobs?

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Quantitative Researcher - Portfolio Management

Arootah

Boston, MA • On-site

$100K - $130K/yr

Full-time

Re-posted 6 days ago

Job description

About the Role
 
Our client, a leading quantitative investment firm, is seeking a Systematic Fixed Income Portfolio Analyst to support its fixed income and macro investment initiatives. This role offers the opportunity to work alongside experienced portfolio managers, quantitative researchers, and technology professionals in a highly analytical, fast-paced environment.
The ideal candidate is intellectually curious, technically skilled, and passionate about applying data-driven analysis to financial markets. This individual will contribute to portfolio analytics, investment research, risk evaluation, and the ongoing enhancement of systematic investment processes.

Key Responsibilities
  • Support portfolio managers and investment teams through quantitative analysis, portfolio monitoring, and market research. 
  • Develop and maintain analytical tools used for portfolio evaluation and risk assessment. 
  • Analyze large datasets to identify trends, anomalies, and actionable investment insights. 
  • Assist in the implementation and refinement of systematic investment approaches across fixed income markets. 
  • Collaborate with technology and research teams to improve workflow automation and reporting capabilities. 
  • Evaluate portfolio exposures and assist with performance attribution and risk analysis. 
  • Produce reporting materials and investment analytics for internal stakeholders. 
  • Contribute to ongoing research projects related to financial markets, portfolio construction, and investment strategy development.
Qualifications
  • Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Finance, Physics, or another quantitative discipline. 
  • 1–4 years of experience in portfolio analytics, quantitative research, investment management, risk analysis, or financial technology. 
  • Familiarity with fixed income products, macroeconomic analysis, or systematic investment strategies is a plus. 
  • Exposure to machine learning, cloud technologies, or data engineering tools is beneficial.
Compensation will be competitive and commensurate with experience. Bonus eligibility included.
Benefits may include:
  • Medical, Dental, and Vision Insurance 
  • 401(k) Retirement Plan 
  • Paid Time Off and Holidays 
  • Professional Development Opportunities 
  • Performance-Based Incentive Compensation 
We may use artificial intelligence (AI) tools to support portions of the hiring process, including resume review and candidate evaluation. These tools assist our recruiting team but do not replace human decision-making. Final hiring decisions are made by human reviewers.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.