GRADE MSRP 0013
LOCATION OF POSITION120 East Baltimore Street
Baltimore, Maryland 21202
Main Purpose of JobThis position serves at the pleasure of the Appointing Authority.The Senior Portfolio Manager/Data Scientist will help develop the data, analytical, and quantitative capabilities that support the Investment Division's research and investment processes.
This position spans quantitative research, data and research infrastructure, machine learning, applied artificial intelligence, and systematic investment analysis. We recognize that candidates may bring different combinations of expertise. The successful candidate is expected to demonstrate substantial strength in one or more core areas, the ability to contribute across related functions, and the capacity to develop adjacent capabilities over time.
The main purpose of this job:
- Lead the development of data, machine learning, and artificial intelligence infrastructure to support scalable quantitative research and investment processes.
- Establish and maintain automated data pipelines and robust data quality controls to ensure the accuracy, timeliness, and integrity of research and production environments.
- Build and maintain comprehensive feature libraries across macroeconomic, cross-asset, equity, and risk domains to facilitate systematic research and portfolio management.
- Conduct quantitative alpha research utilizing advanced statistical, machine learning, and modern AI techniques to generate and enhance predictive signals and investment insights.
- Lead data and technology scouting efforts, partnering with external vendors, research institutions, and industry participants to evaluate emerging technologies and alternative data sources that may contribute to excess returns.
- Support portfolio operations and execution processes, helping ensure efficient implementation and ongoing monitoring of investment strategies.
- Actively participate in macroeconomic and market discussions, assessing their implications across asset classes and contributing to portfolio positioning, particularly during periods of market stress and extreme conditions.
- Provide oversight and management support for internally managed portfolios, including monitoring exposures, risks, performance, and implementation considerations.
- Promote a high-performing, collaborative, and innovation-oriented team culture, fostering knowledge sharing and continuous improvement.
- Collaborate closely with Legal, Operations, Information Systems, Risk, Compliance, and other stakeholders across the Agency to operationalize new capabilities and ensure the successful deployment of investment and technology initiatives.
POSITION DUTIESLead the development of data, machine learning, and artificial intelligence infrastructure to support scalable quantitative research and investment processes. - Build and continuously enhance data, analytics, and ML/AI infrastructure to support quantitative research, signal generation, portfolio construction, and investment decision-making.
- Implement scalable tools and workflows that improve research efficiency, reproducibility, and operational robustness across the investment process.
- Partner with investment, technology, and operations teams to translate research requirements into production-ready capabilities and infrastructure.
Establish and maintain automated data pipelines and robust data quality controls to ensure the accuracy, timeliness, and integrity of research and production environments. - Design, develop, and maintain automated data ingestion and processing pipelines to ensure timely and reliable access to investment data.
- Design, develop and maintain data quality control process to ensure the accuracy, timeliness and integrity of research and production environments.
Conduct quantitative alpha research utilizing advanced statistical, machine learning, and Modern AI techniques to generate and enhance predictive signals and investment insights. - Stay abreast of emerging developments in machine learning, artificial intelligence, and quantitative methodologies, and evaluate their applicability to investment research and portfolio management.
- Develop and apply advanced statistical, machine learning, and AI techniques to macroeconomic, cross-asset, equity, and risk datasets to identify predictive relationships and generate alpha signals.
- Research and model macroeconomic trends, market regimes, asset class returns, and risk dynamics to enhance forecasting and support investment decision-making.
- Build and maintain systematic forecasting frameworks for economic conditions, market environments, and asset price movements across global markets.
- Evaluate model performance and continuously refine methodologies to improve predictive accuracy, robustness, and risk-adjusted investment outcomes.
- Translate research findings into actionable insights that support portfolio construction, risk management, and dynamic asset allocation decisions.
Lead data and technology scouting efforts, partnering with external vendors, research institutions, and industry participants to evaluate emerging technologies and alternative data sources that may contribute to excess returns. - Identify and evaluate emerging technologies, AI capabilities, and alternative data sources that have the potential to enhance investment research and generate excess returns.
- Partner with external vendors, academic institutions, and industry participants to assess innovative datasets, analytical tools, and quantitative methodologies.
- Lead proof-of-concept studies and pilot programs to validate the investment value, scalability, and operational feasibility of new technologies and data solutions.
MINIMUM QUALIFICATIONSEducation: Degree in quantitative discipline such as Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, Economics, or Finance or technical discipline.
Experience: Five years of professional investment experience with three years of experience applying modern AI methodologies to information gathering, processing, forecasting, alpha generation, portfolio construction, and investment decision-making.
DESIRED OR PREFERRED QUALIFICATIONSWe recognize that qualified candidates may bring relevant skills and experience through a variety of professional, educational, and lived experiences. We encourage you to apply even if you do not meet every preferred qualification. We are interested in candidates who can demonstrate the core capabilities required for the role and who are committed to continued learning and professional growth.
Preferred Qualifications: 1) Extensive experience with financial databases, alternative datasets, and data transformation processes.
2) Experience with data engineering, feature engineering, and scalable analytical solutions using Python and modern ML/AI frameworks.
3) Strong expertise in machine learning and artificial intelligence.
4) Knowledge of forecasting, optimization, and portfolio construction techniques used in systematic investing.
5) Ability to integrate quantitative research, and financial market knowledge to develop innovative investment capabilities.
6) Ability to explain complex technical concepts clearly to colleagues with different professional and technical backgrounds.
7) Solid understanding of macroeconomics, equities, fixed income, foreign exchange, commodities, and financial instruments.
SPECIAL REQUIREMENTS A resume and cover letter are required to be uploaded with your application as well as an official transcript.
Due to the confidential nature of the work, selected candidates must undergo and pass a background and credit check.
SELECTION PROCESSPlease make sure that you provide sufficient information on your application to show that you meet the minimum, selective and preferred qualifications for this recruitment. All information concerning your qualifications must be submitted by the closing date. We will not consider information submitted after this date.
Successful candidates will be ranked as Best Qualified, Better Qualified, or Qualified and placed on the employment (eligible) list for at least one year or be placed on a register for at least one year. This list will be used by the hiring agency to select candidates for interviews in-person or virtually.
For education obtained outside the U.S., a copy of the equivalent American education as determined by a foreign credential evaluation service must accompany the application.
EXAMINATION PROCESSThe assessment may consist of a rating of your education, training, and experience related to the requirements of the position. It is important that you provide complete and accurate information on your application. Please report all experience and education that is related to this position
You may be asked to complete a supplemental questionnaire. The supplemental questionnaire may be used as part of the rating process. Therefore, it is important that you provide complete and accurate information on your application.
BARGAINING UNIT STATUS This position is exempt from Bargaining.
BENEFITSLink to
STATE OF MARYLAND BENEFITS As an employee of the State of Maryland, you will have access to outstanding benefits, including, health insurance, dental, and vision plans offered at a low cost.
• Personal Leave - new State employees are awarded six (6) personnel days annually (prorated based on start date).
• Annual Leave - ten (10) days of accumulated annual leave per year.
• Sick Leave - fifteen (15) days of accumulated sick leave per year.
• Holidays - State employees also celebrate at least thirteen (13) holidays per year.
• Pension - State employees earn credit towards a retirement pension.
• Position is eligible for teleworking.
FURTHER INSTRUCTIONSThe online application process is STRONGLY preferred. If you are unable to apply online, you may mail a paper application and supplemental questionnaire to:
Maryland State Retirement and Pension Systems
Human Resources Section
120 E. Baltimore Street
Baltimore, MD 21202
Email Nick Pindale at
[email protected]PLEASE DO NOT SUBMIT UNSOLICITED DOCUMENTATION
The resulting certified eligible list for this recruitment may be used for similar positions in this or other State agencies.