Quantitative Analyst Intern (Contractual) (INVESTMENT ASSOCIATE INTERN)

Introduction

\r\n\r\n\r\n\r\n�\r\n\r\n\r\nThe Maryland State Retirement Agency is the administrator of the Maryland State Retirement and Pension System (“System”). The System is a defined benefit retirement system covering State and local government employees of Maryland. It’s composed of twelve (12) separate retirement and pension systems with over 50 different rule sets. The System has over 433,000 participants (customers), including 210,000 members who are actively employed and participating in the System, 179,000 payees who receive a monthly payment from the System, and 44,000 vested members who are no longer actively employed but have earned a benefit that will become payable at a future date.\r\n\r\n\r\nLocated in Baltimore’s Central Business District, SRPS offers a purpose-driven workplace with modern amenities, including panoramic city and harbor views, renovated common areas, upgraded elevators, and an on-site caf�.\r\n\r\n\r\nEmployees 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.�\r\n\r\n\r\nIf you're seeking a career with impact, stability, and a supportive environment, explore opportunities with MSRPS.\r\n\r\n\r\n\r\n\r\nThe\r\nInvestment Division of the Maryland State Retirement Agency seeks five (5) bright, highly motivated individuals to join\r\nour Quantitative Analyst Internship Program.\r\nEach Intern will have a hands-on opportunity to apply what has been\r\nlearned in the classroom to a real world, large-scale investment operation. �The interns will contribute to quantitative\r\nresearch and analytical projects that support the investment decision-making\r\nprocess. They will gain hands-on experience using industry-leading financial\r\nand data analytics platforms, develop quantitative modeling and programming\r\nskills, and collaborate with investment professionals responsible for managing\r\napproximately $82 billion in assets for the Maryland State Retirement and\r\nPension System as of June 30, 2026.\r\nDates of the Internship\r\nThe start dates of the internship may be flexible. This is part-time employment. The internship will run about a year from the hiring. This internship will follow a hybrid model: a combination of in-person and virtual presence will be required.\r\n\r\n\r\n\r\n

GRADE

HRLY0005\r\n\r\n

LOCATION OF POSITION

\r\n120 East Baltimore Street\r\n\r\n\r\nBaltimore, Maryland 21202\r\n\r\n

Main Purpose of Job

Each Intern will have a hands-on opportunity to apply classroom knowledge within a real world, large-scale institutional investment organization.\r\nSelected interns will contribute to quantitative research, data engineering, machine learning, and artificial intelligence initiatives that support the Investment Division's quantitative research and investment processes. In addition, the interns will assist in establishing and maintaining automated data pipelines and robust data quality controls to ensure the accuracy, timeliness, and integrity of research and production environments, building and maintaining comprehensive feature libraries across macroeconomic, cross-asset, equity, and risk domains to facilitate systematic research and portfolio management, assist in conducting quantitative alpha research utilizing advanced statistical, machine learning, and modern AI techniques to generate and enhance predictive signals and investment insights, and other projects driven by the Investment Division priorities and needs.\r\n

POSITION DUTIES

As an Intern, you will assist in the following:\r\n\r\n Build and continuously enhance\r\n data, analytics, and ML/AI infrastructure to support quantitative\r\n research, signal generation, portfolio construction, and investment\r\n decision-making.\r\n Implement scalable tools and\r\n workflows that improve research efficiency, reproducibility, and\r\n operational robustness across the investment process.\r\n Partner with investment,\r\n technology, and operations teams to translate research requirements into\r\n production-ready capabilities and infrastructure.\r\n Design, develop, and maintain\r\n automated data ingestion and processing pipelines to ensure timely and\r\n reliable access to investment data.\r\n Design, develop and maintain data\r\n quality control processes to ensure the accuracy, timeliness and integrity\r\n of research and production environments.\r\n Stay abreast of emerging\r\n developments in machine learning, artificial intelligence, and\r\n quantitative methodologies, and evaluate their applicability to investment\r\n research and portfolio management.\r\n Develop and apply advanced\r\n statistical, machine learning, and AI techniques to macroeconomic,\r\n cross-asset, equity, and risk datasets to identify predictive\r\n relationships and generate alpha signals.\r\n Research and model macroeconomic\r\n trends, market regimes, asset class returns, and risk dynamics to enhance\r\n forecasting and support investment decision-making.\r\n Assist in development �and enhancement �systematic forecasting frameworks for\r\n economic conditions, market environments, and asset price movements across\r\n global markets.\r\n Evaluate model performance and\r\n continuously refine methodologies to improve predictive accuracy,\r\n robustness, and risk-adjusted investment outcomes.\r\n Translate research findings into\r\n actionable insights that support portfolio construction, risk management,\r\n and dynamic asset allocation decisions\r\n Other Projects, as assigned.\r\n\r\n

MINIMUM QUALIFICATIONS

Education:�Applicants must be currently\r\nenrolled as juniors or seniors in a four-year college or university, or as\r\ngraduate students who have completed at least one semester of graduate-level\r\nstudies, in a quantitative field such as Mathematics, Statistics, Computer\r\nScience, Data Science, Physics, Engineering, Economics, or Finance at the start\r\nof the internship.\r\nIndependent\r\nCoding and AI Proficiency:\r\nDemonstrate strong independent programming skills. We encourage the use of AI\r\ntools and expect quantitative professionals to guide, review, optimize, and\r\nthoroughly validate AI-generated code for accuracy, robustness, and suitability\r\nfor investment applications.\r\nExperience:�No work experience required.\r\n

DESIRED OR PREFERRED QUALIFICATIONS

We welcome\r\ncandidates who have developed relevant investment expertise through different\r\nprofessional paths.� We encourage\r\napplicants to apply who bring strong expertise in one or more core areas,\r\ndemonstrate the ability to learn and contribute to adjacent disciplines, and\r\ncan collaborate effectively across investment, technology, risk, legal,\r\ncompliance, and operational teams.\r\nPREFERRED QUALIFICATIONS\r\n1)\r\nAbility to learn and understand�macroeconomics, equities, fixed income,\r\nforeign exchange, commodities, and financial instruments.\r\n2)\r\nExperience applying modern AI methodologies to information\r\ngathering, processing, forecasting, alpha generation, portfolio construction,\r\nand investment decision-making.\r\n3)\r\nAbility to integrate quantitative research and financial market\r\nknowledge to develop innovative investment capabilities.\r\n4)\r\nAbility to explain complex technical concepts clearly to\r\ncolleagues with different professional and technical backgrounds.\r\n

SPECIAL REQUIREMENTS

A RESUME, MOST\r\nRECENT TRANSCRIPT (OFFICIAL OR UNOFFICIAL ACCEPTED), AND COVER LETTER MUST BE SUBMITTED WITH YOUR APPLICATION IN ORDER TO BE CONSIDERED.\r\n

SELECTION PROCESS

\r\nPlease make sure that you provide sufficient information on your application to show that you meet the minimum for this recruitment.� All information concerning your qualifications must be submitted by the closing date. We will not consider information submitted after this date.\r\n\r\n\r\nSuccessful candidates will be placed on the employment (eligible) list for at least one year. This list will be used by the hiring agency to select employees.�\r\n\r\n\r\nFor education obtained outside the U.S., a copy of the equivalent American education as determined by a foreign credential evaluation service must be provided prior to hire.\r\n\r\n\r\nDue to the confidential nature of the work, selected candidates must undergo and pass a background check.\r\n\r\n

EXAMINATION PROCESS

The assessment\r\nmay consist of a rating of your education, training, and experience related to\r\nthe requirements of the position. It is important that you provide complete and\r\naccurate information on your application.�\r\nPlease report all\r\nexperience and education that is related to this position. You may be asked to\r\ncomplete a supplemental questionnaire. The supplemental questionnaire may be\r\nused as part of the rating process. Therefore, it is important that you provide\r\ncomplete and accurate information on your application.�\r\n

FURTHER INSTRUCTIONS

The online application process is STRONGLY preferred. If you are unable to apply online, you may mail a paper application and supplemental questionnaire to:\r\n�\r\nMaryland State Retirement and Pension Systems\r\nHuman Resources Section\r\n120 E. Baltimore Street\r\nBaltimore, MD 21202\r\nATTN: Ashley Lohr\r\nMust be postmarked by the closing date.\r\nEmail: alohr@sra.state.md.us\r\n�\r\nPLEASE DO NOT SUBMIT UNSOLICITED DOCUMENTATION\r\nThe resulting certified eligible list for this recruitment may be used for similar positions in this or other State agencies.\r\nAs an equal opportunity employer, Maryland is committed to recruiting, retaining and promoting employees who are reflective of the State’s diversity.\r\nPeople with disabilities and bilingual candidates are encouraged to apply.\r\nWe thank our Veterans for their service to our country.\r\n�\r\nTTY Users: call via Maryland Relay\r\n