Senior Portfolio Manager/Data Scientist ***REPOST***

Job Description

Senior Portfolio Manager/Data Scientist ***REPOST***

Sr. Portfolio Manager III MSRP

Recruitment #26-005042-0001

Department

Maryland State Retirement and Pension Systems

Date Opened

8/11/2026 1:33:00 PM

Filing Deadline

8/25/2026 11:59:00 PM

Salary

$194,400.00 - $291,600.00/year

Employment Type

Full-Time

HR Analyst

Nick Pindale

Work Location

Baltimore City

Telework Eligible

Yes

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Introduction

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.

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 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.

MINIMUM QUALIFICATIONS

Education: 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 QUALIFICATIONS

We 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 PROCESS

Please 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

Requirements

MINIMUM QUALIFICATIONS

Education: 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 QUALIFICATIONS

We 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