The board
- Hours
- Full time
- Where
- Boston, MA, United States
- Posted
- Sep 2
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.
THE DEPARTMENT
Investment Implementation & Trading transforms investment decisions into high-quality portfolio implementation across global markets.
What you'd do
- 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.
- Expert-level Python skills for quantitative research, modeling, 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 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.
What they want
- 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.
- Starts
- 2026-07-14