Senior Portfolio Manager/Data Scientist

State of Maryland•Baltimore City, MD

1d•Hybrid

About The Position

The Maryland State Retirement and Pension System (MSRPS) administers benefits for over 430,000 members, including active employees, retirees, and vested participants across 12 retirement systems—supporting the financial security of Maryland’s public servants. Located in Baltimore’s Central Business District, MSRPS offers a purpose-driven workplace with modern amenities, including panoramic city and harbor views, renovated common areas, upgraded elevators, and an on-site café. Employees enjoy comprehensive state benefits including; medical, dental, prescription coverage, generous paid leave, participation in the state pension system, and supplemental retirement savings options (401(k), 457(b), and more). Additional perks include an on-site fitness center with showers and lockers, 24/7 building security, and easy access to restaurants, shops, public transit, and major highways. The Investment Division is committed to an inclusive workplace that values different perspectives, professional backgrounds, educational paths, problem-solving abilities, and lived experiences. We seek to create an environment in which employees are respected, supported, encouraged to contribute openly, and provided meaningful opportunities for development and advancement. This position is designated as telework-eligible under the State of Maryland’s Telework Policy, after successfully completing the defined required training period. GRADE MSRP 0013 LOCATION OF POSITION 120 East Baltimore Street Baltimore, Maryland 21202 Main Purpose of Job This 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. T he 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 DUTIES Lead 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.

Requirements

Five years of professional investment experience
Three years of experience applying modern AI methodologies to information gathering, processing, forecasting, alpha generation, portfolio construction, and investment decision-making.
Degree in quantitative discipline such as Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, Economics, or Finance or technical discipline.

Nice To Haves

Extensive experience with financial databases, alternative datasets, and data transformation processes.
Experience with data engineering, feature engineering, and scalable analytical solutions using Python and modern ML/AI frameworks.
Strong expertise in machine learning and artificial intelligence.
Knowledge of forecasting, optimization, and portfolio construction techniques used in systematic investing.
Ability to integrate quantitative research, and financial market knowledge to develop innovative investment capabilities.
Ability to explain complex technical concepts clearly to colleagues with different professional and technical backgrounds.
Solid understanding of macroeconomics, equities, fixed income, foreign exchange, commodities, and financial instruments.

Responsibilities

Lead 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.
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.

Benefits

medical, dental, prescription coverage
generous paid leave
participation in the state pension system
supplemental retirement savings options (401(k), 457(b), and more)
on-site fitness center with showers and lockers
24/7 building security
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.