Quantitative Trading Analyst Jobs (NOW HIRING)

Wellington Management offers comprehensive investment management capabilities that span nearly all segments of the global capital markets. Our investment solutions, tailored to the unique return and risk objectives of institutional clients in more than 60 countries, draw on a robust body of proprietary research and a collaborative culture that encourages independent thought and healthy debate. As a private partnership, we believe our ownership structure fosters a long‑term view that aligns our perspectives with those of our clients.

Investment Implementation & Trading transforms investment decisions into high-quality portfolio implementation across global markets. The department brings together portfolio construction, global trading, trading research, treasury, middle office, and trading risk management to improve execution quality, trading efficiency, and investment outcomes. Its internally developed trading technology and proprietary data platforms provide a competitive advantage and underpin Wellington's research and electronic trading strategy.

The Trading Research & Analytics (TRA) team is the quantitative research and analytics function supporting Wellington's global trading organization.

We partner directly with traders, portfolio managers, broker‑dealers, and clients to improve execution outcomes through quantitative research, data science, and systematic trading analytics. Our work sits at the intersection of electronic trading, transaction cost analysis, and market microstructure.

Rather than simply measuring trading performance, our mission is to continuously improve it.

We develop the data, models, and research that help answer questions such as:

• Which execution strategy should be used?
• When should an order be executed?
• How much should we expect a trade to cost?
• What execution price should we be willing to pay?
• Which dealers consistently deliver the best outcomes?
• How can systematic trading strategies improve client alpha?

As our trading platform continues to evolve, the team is expanding beyond traditional transaction cost analysis into predictive modeling, execution optimization, and AI‑assisted trading research.

We are seeking a Quantitative Trading Analyst to join Trading Research & Analytics and help improve execution outcomes through research, analytics, and systematic decision support.

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 that improve execution decisions and investment outcomes.

Design and enhance Wellington's fixed income TCA framework, including pre‑ and post‑trade cost models, implementation shortfall analytics, dealer scorecards, execution benchmarking, and best execution reporting. Use quantitative analysis to identify practical opportunities to improve execution quality.

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 to recommend enhancements to Wellington's 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 that combines 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 Wellington's execution strategy, trading technology, and research capabilities.

• Bachelor's degree required; master's or PhD in Statistics, Mathematics, Economics, Computer Science, Engineering, Finance, or a related quantitative discipline considered favorably.
• 5‑7 years of relevant experience in quantitative trading research, execution analytics, TCA, systematic trading, quantitative investment research, or advanced analytics in an institutional markets environment.
• Hands‑on experience supporting institutional fixed income trading, preferably across Investment Grade Credit, High Yield Credit, Emerging Markets Debt, Securitized Credit, or Agency Mortgages.

• Proficient capability in analytics and quantitative research, with experience 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 move beyond reporting into research: 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.

Required:

• Expert‑level Python skills for quantitative research, modelling, data engineering, and production‑quality analytical development, including solid understanding of object‑oriented programming, when to use OOP versus procedural scripts/functions, and how to structure reusable, maintainable code.
• Proficient SQL skills, including fundamentals of querying data with SELECT, WHERE, ORDER BY, COUNT, SUM, AVG, GROUP BY, HAVING, CASE WHEN, and NULL behavior; strong understanding of joins, cardinality, duplicate handling, joins versus subqueries, window functions, and subqueries/CTEs.
• Fluency with modern Python research and modelling 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, with the ability to explain complex analytical findings clearly, tailor messages to technical and non‑technical audiences, and provide 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 in ways that strengthen team dynamics.

Preferred:

• 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/trading data infrastructure is beneficial.

Proficient knowledge in at least one of the following areas, with competent understanding and genuine interest in developing the others: electronic trading, transaction cost analysis, or financial markets knowledge, particularly fixed income market structure. Candidates should understand how trading workflows, order lifecycle, RFQ protocols, dealer behavior, liquidity formation, best execution, and execution/pricing algorithms connect to practical research and analytics problems.

Successful candidates are intellectually curious, pragmatic problem‑solvers who enjoy working at the intersection of trading, technology, and quantitative research. They take ownership from problem definition through implementation, balancing scientific rigor with practical business impact. They enjoy building production‑quality analytical software and understand that elegant research is only valuable when it improves real trading decisions. They are comfortable working with imperfect real‑world data, naturally curious about how markets function, and motivated by improving trading outcomes through research, analytics, and innovation.

They thrive in collaborative environments where success depends on partnering effectively with traders, portfolio managers, technologists, and external market participants to transform quantitative insights into better investment decisions.

This role provides the opportunity to help shape the future of trading at one of the world's largest institutional asset managers.

Rather than focusing solely on reporting historical performance, you will help develop the predictive analytics, systematic trading capabilities, and decision‑support tools that define the next generation of portfolio implementation.

You will work directly alongside traders, portfolio managers, technologists, and quantitative researchers to improve execution quality across global fixed income markets and contribute to a platform that continues to evolve through data, research, and innovation.

As an equal opportunity employer, Wellington Management ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, sex, sexual orientation, gender identity, gender expression, religion, creed, national origin, age, ancestry, disability (physical or mental), medical condition, citizenship, marital status, pregnancy, veteran or military status, genetic information or any other characteristic protected by applicable law . If you are a candidate with a disability, or are assisting a candidate with a disability, and require an accommodation to apply for one of our jobs, please email us at GMWTalentOperations@wellington.com.

At Wellington Management, our approach to compensation is designed to help us attract, inspire and retain the best talent in our industry. We strive to pay employees fairly and competitively across all levels and roles. Our approach to compensation considers all aspects of total compensation; all employees are eligible to receive salary, variable compensation, and benefits. The base salary range for this position is: USD 90,000 - 180,000

Base salary is only one component of Wellington's total compensation approach. Other rewards may include a discretionary Corporate Bonus and/or Incentives, if eligible. In addition, we offer a comprehensive and high value benefit package to meet the unique needs of our employees and their families, and we are committed to fostering a flexible work environment that enables employees to thrive personally and professionally. Examples of our benefits include retirement plan, health and wellbeing, dental, vision, and pharmacy coverage, health savings account, flexible spending accounts and commuter program, employee assistance program, life and disability insurance, adoption assistance, back‑up childcare, tuition/CFA reimbursement and paid time off (leave of absence, paid holidays, volunteer, sick and vacation time)

We believe that in person interactions inspire and energize our community and are essential to our culture. In support of this commitment, our employees work from our offices 4 days a week with flexibility to work remotely 1 day a week. We believe that this approach ultimately supports our mission to deliver investment excellence to our clients and their beneficiaries over the long term.