STEM OPT Quantitative Research Analyst Jobs
Quantitative Research Analyst roles sit squarely within STEM-designated fields, making them strong fits for F-1 students seeking the 24-month STEM OPT extension. Your employer must be enrolled in E-Verify, and your degree in mathematics, statistics, computer science, or a related STEM field must map to an eligible CIP code to qualify.
Find STEM OPT Quantitative Research Analyst JobsOverview
Showing 5 of 473+ Quantitative Research Analyst jobs
See all 473+ Quantitative Research Analyst Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Quantitative Research Analyst roles.
Get Access To All JobsJob Description:
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
GRA About Us Summary
Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM). The GRA team provides quantitative capabilities supporting global risk management and capital management and develops a consistent set of risk and capital models, tests and analytical tools that support decision making across the bank.
Job Profile Summary
This job is responsible for building subject matter expertise in bank processes - including underlying data, flows, and controls - and driving the technology evolution in those processes including designing and implementing technical solutions leveraging modular, reusable software components to enhance Global Risk Management’s (GRM) data, testing, and analytical capabilities.
Key responsibilities include collaborating with process owners, risk managers, and technologists to assess current state processes, underlying data, process flows and risks, and to design the future state technology solutions leveraging both traditional and AI based solutions. Job expectations include becoming domain-specific subject matter expert in bank processes and data, and applying a combination of software engineering, big data, data science and risk management skills to drive technical solution implementation and automate processes.
Responsibilities
- Analytical Thinking & Risk Management: Apply critical thinking, sound judgment, risk management principles to understand business processes, controls, and risks to determine appropriate designs for technical solutions to business problems.
- Stakeholder Engagement & Communication: Partner with process owners, data owners, Front Line Units, Technology teams, and other stakeholders to understand business requirements, influence outcomes, communicate technical designs, and impact of solutions to audiences ranging from practitioners to senior executives.
- Solution Development & Engineering: Leverage programming expertise, software development lifecycle (SDLC) principles, and AI development patterns to design, build, document, and deploy scalable analytical solutions that support business objectives, regulatory requirements, and operational efficiency.
- Data Engineering & Analytics: Source, validate, and analyze data while designing scalable data pipelines and analytical solutions across large and complex datasets. Apply quantitative and analytical techniques to identify trends, assess risk, and enhance the firm’s data architecture.
- AI Governance & Operational Excellence: Implement governance, security, observability, and auditability controls for AI-enabled solutions while continuously monitoring performance, driving process optimization, and enhancing solution effectiveness through testing, feedback loops, automation, and responsible AI adoption.
Minimum Education Requirements
- Bachelor’s degrees or above in fields including but not limited to: Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science (or equivalent work experience)
- At least 2 years of relevant experience in software engineering in Quantitative Finance or other industries
Required Skills
- Analytical Thinking & Problem Solving: Applies structured thinking, quantitative analysis, and sound judgment to solve complex business, risk, data, and technology challenges while driving continuous improvement and innovation.
- Communication & Stakeholder Management: Effectively communicates complex technical concepts to different audiences and able to build strong partnerships across stakeholders.
- Software Engineering & AI Development: Demonstrates proficiency in Python and software development best practices, including SDLC, testing frameworks, design patterns, performance optimization, and the development of AI-enabled solutions using modern LLM platforms, agent frameworks, RAG, and MCP patterns.
- Data Engineering & Analytics: Strong experience working with structured and unstructured data, SQL, APIs, and databases to source, analyze, and integrate data while solving complex analytical problems at scale.
- AI Governance & Performance Monitoring: Applies responsible AI practices and evaluates AI solution performance through monitoring, testing, reliability measurement, scalability assessments, and continuous optimization of cost, quality, and user outcomes.
- Business & Regulatory Knowledge: Demonstrates knowledge of banking processes, risk management principles, and regulatory requirements, applying business context to deliver effective and compliant solutions.
Skills:
- Critical Thinking
- Data Modeling
- Process Effectiveness
- Risk Modeling
- Test Engineering
- Influence
- Oral Communications
- Prioritization
- Relationship Building
- Written Communications
- Attention to Detail
- Change Management
Shift:
1st shift (United States of America)
Hours Per Week:
40
Job Description:
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
GRA About Us Summary
Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM). The GRA team provides quantitative capabilities supporting global risk management and capital management and develops a consistent set of risk and capital models, tests and analytical tools that support decision making across the bank.
Job Profile Summary
This job is responsible for building subject matter expertise in bank processes - including underlying data, flows, and controls - and driving the technology evolution in those processes including designing and implementing technical solutions leveraging modular, reusable software components to enhance Global Risk Management’s (GRM) data, testing, and analytical capabilities.
Key responsibilities include collaborating with process owners, risk managers, and technologists to assess current state processes, underlying data, process flows and risks, and to design the future state technology solutions leveraging both traditional and AI based solutions. Job expectations include becoming domain-specific subject matter expert in bank processes and data, and applying a combination of software engineering, big data, data science and risk management skills to drive technical solution implementation and automate processes.
Responsibilities
- Analytical Thinking & Risk Management: Apply critical thinking, sound judgment, risk management principles to understand business processes, controls, and risks to determine appropriate designs for technical solutions to business problems.
- Stakeholder Engagement & Communication: Partner with process owners, data owners, Front Line Units, Technology teams, and other stakeholders to understand business requirements, influence outcomes, communicate technical designs, and impact of solutions to audiences ranging from practitioners to senior executives.
- Solution Development & Engineering: Leverage programming expertise, software development lifecycle (SDLC) principles, and AI development patterns to design, build, document, and deploy scalable analytical solutions that support business objectives, regulatory requirements, and operational efficiency.
- Data Engineering & Analytics: Source, validate, and analyze data while designing scalable data pipelines and analytical solutions across large and complex datasets. Apply quantitative and analytical techniques to identify trends, assess risk, and enhance the firm’s data architecture.
- AI Governance & Operational Excellence: Implement governance, security, observability, and auditability controls for AI-enabled solutions while continuously monitoring performance, driving process optimization, and enhancing solution effectiveness through testing, feedback loops, automation, and responsible AI adoption.
Minimum Education Requirements
- Bachelor’s degrees or above in fields including but not limited to: Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science (or equivalent work experience)
- At least 2 years of relevant experience in software engineering in Quantitative Finance or other industries
Required Skills
- Analytical Thinking & Problem Solving: Applies structured thinking, quantitative analysis, and sound judgment to solve complex business, risk, data, and technology challenges while driving continuous improvement and innovation.
- Communication & Stakeholder Management: Effectively communicates complex technical concepts to different audiences and able to build strong partnerships across stakeholders.
- Software Engineering & AI Development: Demonstrates proficiency in Python and software development best practices, including SDLC, testing frameworks, design patterns, performance optimization, and the development of AI-enabled solutions using modern LLM platforms, agent frameworks, RAG, and MCP patterns.
- Data Engineering & Analytics: Strong experience working with structured and unstructured data, SQL, APIs, and databases to source, analyze, and integrate data while solving complex analytical problems at scale.
- AI Governance & Performance Monitoring: Applies responsible AI practices and evaluates AI solution performance through monitoring, testing, reliability measurement, scalability assessments, and continuous optimization of cost, quality, and user outcomes.
- Business & Regulatory Knowledge: Demonstrates knowledge of banking processes, risk management principles, and regulatory requirements, applying business context to deliver effective and compliant solutions.
Skills:
- Critical Thinking
- Data Modeling
- Process Effectiveness
- Risk Modeling
- Test Engineering
- Influence
- Oral Communications
- Prioritization
- Relationship Building
- Written Communications
- Attention to Detail
- Change Management
Shift:
1st shift (United States of America)
Hours Per Week:
40
See all 473+ STEM OPT Quantitative Research Analyst Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Quantitative Research Analyst Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Quantitative Research Analyst
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code appears on the STEM OPT designated degree program list. Statistics, applied mathematics, financial engineering, and computer science programs almost always qualify, but interdisciplinary degrees sometimes don't.
Confirm E-Verify enrollment before accepting offers
Ask recruiters directly whether the firm is enrolled in E-Verify before you invest time in later interview rounds. Hedge funds and boutique quant shops sometimes aren't enrolled, even when they're otherwise willing to hire OPT students.
Use Migrate Mate to target verified sponsors
Search Quantitative Research Analyst roles on Migrate Mate, which filters for employers with confirmed STEM OPT hiring history. This cuts out the guesswork of cold-applying to firms that have never filed for OPT students.
Benchmark your offer against DOL prevailing wages
Pull the wage level for your specific role and metro area using the OFLC Wage Search before you negotiate. Employers filing a training plan under STEM OPT must pay you the prevailing wage for your occupation, so knowing Level II or III rates gives you a factual baseline.
File your I-983 training plan before your OPT end date
Work with your DSO to submit the I-983 at least 90 days before your initial OPT expires. Quantitative research roles must describe specific learning objectives tied to your STEM degree, not generic job duties, or USCIS can reject the plan.
Understand cap-gap coverage if you're H-1B selected
If your employer files an H-1B visa petition and you're selected in the lottery, cap-gap automatically extends your STEM OPT work authorization through September 30. Confirm your employer intends to file in March so you can plan your authorization timeline accurately.
Frequently Asked Questions
Does a Quantitative Research Analyst role qualify for the STEM OPT extension?
Yes, in most cases. The role falls under SOC codes tied to mathematical science and operations research occupations, which are covered by STEM OPT. Your degree, not just your job title, must also map to an eligible CIP code on the STEM designated degree program list. Degrees in statistics, applied mathematics, financial engineering, and computer science routinely qualify. Confirm your specific CIP code with your DSO before filing.
What does my employer need to do to support my STEM OPT?
Your employer must be enrolled in E-Verify and must sign the I-983 training plan alongside you. The plan requires them to describe specific technical skills and learning objectives your role will develop, not just list your job duties. They also must attest that you'll be paid at least the prevailing wage for your occupation and location, as determined by DOL wage data. Employers who have never hired STEM OPT students before sometimes underestimate this paperwork burden.
How do I find Quantitative Research Analyst positions where the employer is already enrolled in E-Verify?
Migrate Mate filters for employers with confirmed STEM OPT hiring history, so you can focus on firms that are already enrolled in E-Verify and familiar with the I-983 process. This matters especially in the quant space, where many boutique hedge funds and prop trading firms are willing to hire but haven't completed E-Verify enrollment, which disqualifies them as STEM OPT employers regardless of intent.
What happens to my STEM OPT if my employer's E-Verify enrollment lapses?
Your STEM OPT authorization is tied to your employer maintaining active E-Verify enrollment throughout your extension period. If enrollment lapses, you're technically out of status even if you continue working. USCIS requires ongoing compliance, not just enrollment at the time of filing. Verify your employer's E-Verify status with your DSO periodically, and confirm it again before each annual I-983 attestation.
What happens to my work authorization if I'm selected in the H-1B lottery while on STEM OPT?
Cap-gap protection automatically extends your STEM OPT work authorization if your employer files an H-1B petition on your behalf and you're selected. Your authorization continues through September 30 of that year, bridging the gap until the H-1B start date of October 1. Your employer must file the petition before your STEM OPT expires for cap-gap to apply. Confirm the filing timeline with your employer well before the March registration window closes.