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Wellington Management

Global asset management for institutional clients

Quantitative Trading Analyst

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-timeBoston, MA, USA

About the Job

Requirements

  • A bachelor's degree is required; a master's or PhD in Statistics, Mathematics, Economics, Computer Science, Engineering, Finance, or a related quantitative discipline is favorably considered.
  • Five to seven years of relevant experience in quantitative trading research, execution analytics, transaction cost analysis, systematic trading, quantitative investment research, or advanced analytics in an institutional markets environment.
  • Hands-on experience supporting institutional fixed income trading is required; experience across Investment Grade Credit, High Yield Credit, Emerging Markets Debt, Securitized Credit, or Agency Mortgages is preferred.
  • Proficient capability in analytics and quantitative research, including cleaning messy real-world data, developing visualizations, generating reports, and using descriptive analytics to explain what happened and diagnostic analytics to explain why it happened.
  • Ability to formulate trading, execution, liquidity, and portfolio implementation questions as testable hypotheses using statistics, algebra, mathematical reasoning, and data-driven inference.
  • Hands-on experience building, validating, and interpreting predictive models, transaction cost models, optimization frameworks, machine learning models, or AI-assisted research workflows used in trading or execution analytics.
  • Experience analyzing real-world trading datasets, including orders, executions, quotes, dealer responses, benchmarks, prices, liquidity signals, and portfolio attributes.
  • Interest in applying machine learning, natural language processing, or modern AI techniques to trading research, predictive analytics, data quality, automation, or decision support.
  • Expert-level Python skills for quantitative research, modeling, data engineering, and production-quality analytical development, including understanding object-oriented programming and when to use object-oriented programming versus procedural scripts or functions, and structuring reusable, maintainable code.
  • Proficient SQL skills, including SELECT, WHERE, ORDER BY, COUNT, SUM, AVG, GROUP BY, HAVING, CASE WHEN, and NULL behavior; understanding joins, cardinality, duplicate handling, joins versus subqueries, window functions, and subqueries or common table expressions.
  • Fluency with modern Python research and modeling libraries, including pandas for real-world and messy data, NumPy for vectorized thinking, and scikit-learn for machine learning workflows.
  • Experience using Git, reproducible research workflows, code review, testing, and documentation to maintain analytical rigor and reliability.
  • Proficient time management and prioritization, demonstrated through evidence-based examples of organizing work, protecting focus during interruptions, managing competing priorities, and delivering reliably in a fast-moving trading environment.
  • Proficient communication skills, including explaining complex analytical findings clearly, tailoring messages to technical and non-technical audiences, and providing evidence-based examples of effective stakeholder communication.
  • Expert collaboration skills, including acting on feedback, providing constructive feedback to colleagues, sharing knowledge, contributing to collective learning, and constructively handling differences of opinion.
  • Proficient knowledge in at least one of electronic trading, transaction cost analysis, or financial markets knowledge, particularly fixed income market structure, and competent understanding and genuine interest in developing the other areas. Candidates should understand how trading workflows, order lifecycle, RFQ protocols, dealer behavior, liquidity formation, best execution, and execution or pricing algorithms connect to practical research and analytics problems.

Responsibilities

  • Conduct empirical research on trading behavior, market microstructure, liquidity, and execution performance across global fixed income markets; translate ambiguous business questions into testable research hypotheses and develop statistical, optimization, and machine learning models to improve execution decisions and investment outcomes.
  • Design and enhance the fixed income transaction cost analysis framework, including pre- and post-trade cost models, implementation shortfall analytics, dealer scorecards, execution benchmarking, and best execution reporting; identify practical opportunities to improve execution quality through quantitative analysis.
  • Partner with fixed income traders to analyze execution across Global Investment Grade Credit, Global High Yield, Emerging Markets Debt, Securitized Credit, and Agency Mortgages; track market structure, electronic trading, dealer behavior, RFQ protocols, and liquidity trends and recommend enhancements to trading capabilities.
  • Build research and analytical tools that help traders and portfolio managers make better execution decisions; evaluate execution strategies, dealer selection, liquidity conditions, and timing to support systematic trading workflows and improve outcomes.
  • Own the analytical representation of trading data and partner with technology teams to build scalable research datasets across the trading lifecycle.
  • Maintain production-quality research infrastructure combining OMS, EMS, market, pricing, and portfolio data with strong data quality, business logic, reproducibility, and analytical integrity.
  • Collaborate with portfolio managers, traders, broker-dealers, technology teams, and senior leaders to translate research into practical trading decisions.
  • Communicate complex findings clearly and help shape execution strategy, trading technology, and research capabilities.

Desired Qualifications

  • Experience with JIRA or business intelligence tools such as Tableau is preferred; these skills can be developed on the job where the candidate demonstrates strong learning agility.
  • Additional experience with APIs, FIX protocol, cloud data platforms, distributed data processing, or market and trading data infrastructure is beneficial.

About the Company

Wellington Management

Global asset management for institutional clients

Wellington Management is a global investment management firm that offers equity, fixed income, multi-asset, and alternative investments to both institutional clients (such as pension funds, endowments, foundations, and insurers) and individual investors. It manages assets on behalf of clients, earning fees based on assets under management (AUM) and on investment performance. The firm relies on deep research capabilities and market insights to tailor investment strategies that meet client needs, and it integrates environmental, social, and governance (ESG) factors into its process. What sets Wellington Management apart is its broad suite of investment options combined with a commitment to ESG integration and a client-tailored approach, supported by a culture that emphasizes diversity and inclusion. The company’s goal is to help clients achieve their investment objectives by delivering disciplined, research-driven strategies and sustainable investing over the long term.

Company size
1,001-5,000
Company stage
Not listed
Total funding
$66.9B
Headquarters
Boston, MA
Founded
1933

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