STEM OPT Quantitative Jobs
Quantitative roles in finance, risk, and data science are among the strongest matches for STEM OPT students with degrees in mathematics, statistics, or computer science. Your 24-month STEM OPT extension applies here, provided your employer is enrolled in E-Verify and your role ties directly to your STEM degree field.
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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 Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization in Quantitative
Verify your CIP code covers quant roles
Your STEM OPT eligibility depends on your degree's CIP code, not just your field name. Confirm your DSO has coded your program correctly, since mathematics, statistics, and financial engineering CIP codes each map differently to quantitative analyst roles.
Check E-Verify enrollment before applying
Every employer who hires you on STEM OPT must be enrolled in E-Verify. Ask recruiting contacts directly whether the legal entity making your offer is enrolled, not just the parent company, since subsidiaries sometimes have separate E-Verify accounts.
Use O*NET to document your role qualifications
Before your I-983 training plan is drafted, look up your quantitative job title in O*NET to pull the official occupation description and required knowledge areas. This gives your employer concrete language to justify how the role connects to your STEM degree.
Anchor your I-983 to quant-specific learning goals
Generic I-983 training plans get flagged during USCIS audits. For quantitative roles, your learning objectives should reference specific skills like stochastic modeling, algorithmic strategy, or derivatives pricing that directly map to your degree coursework.
Target employers with quant-heavy LCA filing history
Use Migrate Mate to filter for employers who have filed Labor Condition Applications for quantitative analyst and related roles, so you're applying to firms with a documented record of sponsoring STEM OPT students in this function rather than guessing from job postings.
File your STEM OPT extension 90 days before OPT expires
Your DSO must recommend the STEM OPT extension in SEVIS, and USCIS must receive the I-765 before your initial OPT EAD expires. Filing at the 90-day window gives you cap-gap protection if an H-1B visa petition is filed on your behalf before October 1.
Frequently Asked Questions
Do quantitative analyst roles qualify for the STEM OPT extension?
Yes, provided your degree is in a qualifying STEM field such as mathematics, statistics, financial engineering, or computer science, and the quantitative role directly applies that training. Your DSO verifies eligibility based on your program's CIP code. Roles in algorithmic trading, risk modeling, and quantitative research consistently qualify when the degree-to-job connection is documented in the I-983 training plan.
What does my employer need to do to support my STEM OPT?
Your employer must be enrolled in E-Verify at the specific legal entity making your offer, not just a parent organization. They also co-sign your I-983 training plan, which outlines your learning objectives, supervision structure, and how the quantitative role connects to your STEM degree. USCIS may audit I-983 plans, so the training goals should be specific to your actual job duties, not a generic description.
How do I find quantitative employers enrolled in E-Verify?
Job postings rarely list E-Verify status, so you need a way to filter before applying. Migrate Mate shows employers with verified E-Verify enrollment alongside their LCA filing history for quantitative roles, so you can confirm eligibility before reaching the offer stage. You can also ask a recruiter directly which legal entity is making the offer and whether that entity is E-Verify enrolled.
What happens to my work authorization if I'm selected in the H-1B lottery during STEM OPT?
If your employer files an H-1B petition on your behalf before your STEM OPT EAD expires, cap-gap provisions extend your work authorization automatically through September 30 of that year, or until USCIS issues a final decision on your petition. You can continue working in your quantitative role during this period without interruption. USCIS confirms cap-gap eligibility on your I-20.
Can I switch quantitative employers while on STEM OPT?
Yes, but the new employer must also be enrolled in E-Verify, and you must file an updated I-983 training plan with your DSO within ten days of starting. Your DSO reports the employer change in SEVIS. If the new role is at a different employer type, such as a hedge fund versus a bank, confirm that your STEM degree still maps to the new job duties before filing the updated plan.