Public Market Analytics Senior Analyst

Teacher Retirement System of Texas (TRS)•Austin, TX

6d•Onsite

About The Position

The Public Market Analytics team within the Investment Management Division is building the analytical foundation that helps portfolio managers, researchers, and senior leaders make better investment decisions across Public Markets strategies. This role is an opportunity to sit at the intersection of investments, data, technology, and research—turning complex portfolio, benchmark, risk, and market data into clear, actionable insights. The Senior Analyst will help deliver high-impact portfolio analytics, including performance attribution, factor exposures, risk decomposition, and recurring executive-quality reporting. The role will also contribute to the design and scaling of modern analytics infrastructure, including automated workflows, data pipelines, dashboards, validation processes, and reusable tools built with technologies such as Python, SQL, and Power BI. This is an ideal opportunity for a quantitatively minded investment professional who enjoys solving data-intensive problems, building production-quality analytics, and translating technical analysis into practical portfolio insights. The successful candidate will partner closely with portfolio managers, researchers, and technology teams to improve data quality, enhance analytical frameworks, and expand the team’s ability to evaluate performance, understand risk, identify opportunities, and support better portfolio construction decisions.

Requirements

Bachelor’s degree from an accredited college or university in quantitative discipline such as finance, economics, statistics, mathematics, financial engineering, or data science or a closely related field.
One (1) year of full-time directly related, progressively responsible experience in a professional capacity requiring a high degree of skill in data analysis, financial analytics, or quantitative modeling, or related experience.
One (1) year of full-time directly related, progressively responsible experience working with financial data, portfolio analytics, or investment-related datasets, including performance and/or risk analysis, or related experience.
Experience may be concurrent.
A master's degree or doctoral degree in a closely related field may be substituted on an equivalent year-for-year basis.
Statistical and analytical techniques, including performance attribution, risk decomposition, factor analysis, and portfolio analytics.
Financial markets, investment concepts, and systematic equity strategies, including familiarity with portfolio construction, benchmarking, and risk frameworks.
Programming and data analysis tools, including Python, SQL, and related libraries used for data manipulation, analytics, and automation.
Data engineering concepts, including data pipelines, ETL processes, data integration, and data quality management.
Data visualization and reporting tools (e.g., Power BI, Tableau, or similar), and principles of effective data presentation and communication.
Conducting analysis of large and complex datasets, including financial and portfolio data, and synthesizing outputs into clear and actionable insights.
Developing, maintaining, and enhancing analytical tools, reports, dashboards, and data pipelines with a high degree of accuracy and attention to detail.
Identifying, troubleshooting, and resolving data and analytics issues, including data inconsistencies, model discrepancies, and reporting gaps.
Planning, organizing, and prioritizing work assignments to manage multiple deliverables in a fast paced environment while maintaining high-quality output.
Communicating complex analytical and technical concepts clearly and effectively through written reports, presentations, and discussions with both technical and non-technical stakeholders.
Work collaboratively in a cross-functional environment with portfolio managers, researchers, and technology teams to support investment decision-making.
Translate complex analytical outputs into practical insights that inform portfolio construction, risk management, and investment strategy evaluation.
Learn and adapt quickly in a dynamic investment and data environment, including adopting new tools, technologies, and analytical methodologies.
Manage multiple priorities and deadlines while maintaining a high level of accuracy, accountability, and attention to detail.
Contribute to the development and scaling of analytics, reporting, and data infrastructure in a production environment.

Nice To Haves

Master’s degree from an accredited college or university in quantitative discipline such as finance, economics, statistics, mathematics, financial engineering, or data science or a closely related field.
Two (2) years of full-time directly related, progressively responsible experience in a professional capacity requiring a high degree of skill in data analysis, financial analytics, or quantitative modeling, or related experience.
Experience with programming languages such as Python, SQL, R, or similar, including experience working with large datasets and data manipulation.
Experience developing, enhancing, or maintaining analytical reports, dashboards, or data pipelines.
Experience with investment analytics, including performance attribution, risk decomposition, factor analysis, or portfolio exposure analysis.
Familiarity with risk and analytics platforms (e.g., Barra, Axioma, FactSet, or similar tools).

Responsibilities

Deliver comprehensive portfolio analytics including performance attribution (multi-level), factor exposures, risk decomposition, and benchmarking analysis across equity strategies.
Produce consistent, high-quality recurring reports (daily, weekly, monthly) as well as ad hoc deep-dive analysis for portfolio managers and senior leadership.
Analyze and explain drivers of performance and risk, including factor contributions, sector/country effects, and unintended exposures.
Partner with PMs and researchers to translate analytical outputs into actionable insights that inform portfolio construction and positioning decisions.
Ensure data integrity, accuracy, and timeliness of all analytics outputs, implementing validation checks and reconciliation processes.
Continuously improve reporting frameworks to enhance clarity, usability, and decision relevance for stakeholders.
Design, build, and maintain scalable data pipelines and ETL processes integrating multiple internal and external data sources (market data, holdings, benchmarks, risk models).
Develop and enhance analytics tooling using Python, SQL, and Power BI to automate workflows and reduce manual processes.
Partner with technology and data teams to improve data architecture, governance, and quality controls, ensuring consistency across platforms.
Optimize performance of analytics processes to support large-scale data processing and timely delivery.
Contribute to the build-out of next-generation analytics infrastructure, including standardized data models and reusable components.
Troubleshoot data and system issues, ensuring robustness and reliability of production analytics pipelines.
Support research efforts related to factor exposures, risk models, portfolio construction, and investment strategy evaluation.
Conduct exploratory analysis on market behavior, factor performance, and portfolio characteristics to identify risks and opportunities.
Assist in the development and enhancement of analytical frameworks, methodologies, and tools used by Public Markets investment teams.
Prepare clear, concise presentations and written summaries of findings tailored to both technical and non-technical audiences.
Collaborate cross-functionally with research, PM, and technology teams to translate research outputs into production-ready analytics.