Quantitative Developer, IDEA Team

About the Role

The Team – Investment Data Engineering & Analytics (IDEA)

The Investment Data Engineering & Analytics (IDEA) team sits within the Investment Platform (IP) COO organization. The IP COO group is responsible for enabling the Investment Platform to achieve its growth and efficiency goals by creating scalable centers of excellence, aligning with business needs, and integrating business and technology strategies.

As data continues to grow in importance as an enabler of the investment process, the IDEA team is responsible for evolving the firm’s research data and analytics platform. The team partners closely with investors, technologists, and enterprise data functions to build and sustain a platform that provides seamless access to a library of foundational research data and analytics across asset classes.

The Position

We are seeking a Quantitative Developer to join the IDEA team and help design, build, and extend our central research data platform. This individual will work primarily in Python and modern cloud data technologies to build the full stack of investment data and analytics: from transforming raw vendor and internal data into clean, well-modeled, investment-ready datasets to tools that power fundamental and systematic research.

The ideal candidate combines strong Python engineering skills, a deep interest in data modeling and architecture, and a practical understanding of investment data and how investors use it. This person is energized by building in a dynamic environment, comfortable with ambiguity, and motivated by the opportunity to create structure from complexity.

This role will work closely with both fundamental and quantitative investors and researchers, technology partners, and enterprise data teams.

Key Responsibilities

• Design and implement robust data models for securities, issuers, fundamentals, time series, and analytics across multiple asset classes (e.g., equity, fixed income, macro).
• Develop and maintain Python-based libraries and services that provide consistent, well-documented access to research data and analytics.
• Partner with data engineering to ensure upstream data and pipelines support analytics needs.
• Collaborate with investors and quantitative researchers to understand their workflows and translate requirements into scalable data and tooling solutions.
• Contribute to the rationalization of data vendors and the convergence of legacy data stores into a cohesive, central platform capability.
• Implement and enhance data and analytics quality controls, monitoring, and documentation to promote trust in both the data and the analytics built on top of it.
• Participate in code reviews, design discussions, and standards-setting to ensure high engineering quality and reusability across the platform.
• Proactively identify opportunities to improve performance, usability, and reliability of the platform, and drive initiatives from concept through to adoption.

Required Skills & Qualifications

Technical skills

• Strong hands-on experience with Python for data-intensive applications, including use of common libraries (e.g., pandas, polars, numpy) and building testable, maintainable, production-quality code.
• Solid understanding of data modeling concepts, particularly for time-series and reference data (e.g. slowly changing dimensions, point-in-time and bi-temporal data).
• Proficiency with SQL and experience working with large datasets in modern data platforms (e.g., Snowflake, cloud data warehouses, data lakes) and open-source formats such as parquet.
• Strong software engineering fundamentals: version control (git), code reviews, unit/integration testing, logging, and documentation.

Domain knowledge

• Working knowledge of investment data, including:Security master and symbology (e.g., issuer vs. security identifiers, vendor symbologies).Fundamental data (e.g., financial statements, estimates), pricing and returns, benchmarks, and basic risk/portfolio concepts.
• Familiarity with the practical use of data in investment workflows such as screening, backtesting, portfolio analysis, factor, and performance / attribution concepts.

Experience & Education

• 3-7 years of professional experience as a quantitative developer, quantitative analyst, or research platform/analytics engineer in asset management, a hedge fund, or a similarly data-driven financial environment.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field, or equivalent professional experience.

Not sure you meet 100% of our qualifications? That’s ok. If you believe that you could excel in this role, we encourage you to apply and welcome a chance to review your background. We are dedicated to building and maintaining a diversified workforce and considering a broad array of candidates with a variety of skill, workplace experiences, and backgrounds.

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 .

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

This range takes into account the wide range of factors that are considered when making compensation decisions, including but not limited to skill sets; role; skills and experience; certifications; and education. This range is an estimate, and further details on salary and total compensation aspects will be shared with candidates during the recruitment process.

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/CFAreimbursement 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.