Data Scientist Visa Sponsorship Jobs in North Carolina
Data scientist roles in North Carolina are concentrated in the Research Triangle, where employers like SAS Institute, IBM, and Lenovo regularly hire for advanced analytics positions. The state's dense network of research universities, pharmaceutical companies in Durham, and growing fintech presence in Charlotte make it one of the more active markets for visa-sponsored data science work.
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Get Access To All JobsINTRODUCTION
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!
ROLE AND RESPONSIBILITIES
This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.
Responsibilities:
- Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights
- Applies agile practices for project management, solution development, deployment, and maintenance
- Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production
- Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment
- Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
- Mitigates risk by identifying potential issues and developing controls
- Researches the latest advances in the fields of data science and artificial intelligence to support business analytics
Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities.
Overview of Data Science for Technology, Risk and Operations:
Data Science for Technology, Risk, and Operations (DSTRO) enables the Bank's responsible adoption of Artificial Intelligence (AI) through governance, model oversight, model development, and enterprise data engineering. By providing AI and model risk governance, AI-driven solutions, and critical transaction data assets, DSTRO delivers the controls, infrastructure, and insights needed to strengthen risk management, enhance operational effectiveness, and drive enterprise value.
As a Data Scientist I supporting the THOR Data Engineering team and Enterprise AI Catalyst program, you will contribute to the development, enhancement, and maintenance of data, AI, and model solutions that address business needs across the enterprise. Working with senior model owners, developers, users, and cross-functional partners, you will analyze large-scale financial transaction data, investigate data patterns and anomalies, develop and validate value-added attributes, and support solutions throughout the product lifecycle, from ideation and testing through production and retirement.
Using SQL and other analytical and data science tools, you will help deliver scalable, compliant solutions that improve decision-making, streamline processes, and support business applications including revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. You will also identify opportunities to leverage and reuse existing AI technologies, models, data assets, and methodologies to reduce duplication and promote best practices.
The role will support THOR product enhancements, quality assurance, production validation, user analytics, technical documentation, training, and informational presentations. Success requires strong analytical and data science capabilities, attention to detail, intellectual curiosity, and effective relationship and project management skills.
Key Responsibilities:
- Support the development, enhancement, and maintenance of THOR data, AI, and model solutions throughout the product lifecycle.
- Analyze large-scale transaction data using SQL and other analytical tools to identify patterns, anomalies, risks, and opportunities.
- Develop, evaluate, audit, and validate transaction categorizations, value-added attributes, and product enhancements.
- Apply established quality-control, testing, documentation, and post-production validation practices.
- Partner with model owners, developers, users, and business teams to understand requirements and deliver scalable, compliant solutions.
- Identify opportunities to reuse existing AI technologies, models, data assets, and methodologies across the enterprise.
- Support analytical requests, user documentation, training materials, and presentations for the THOR user community.
BASIC QUALIFICATIONS
- Data Analysis
- Data Cleansing
- Data Quality and Validation
- Agile Practices
- Technical Documentation
- Written Communications
- Research and Analytical Methods
- Data management
- Data Visualization
- Presentation Skills
- Risk Awareness
- Adaptability
- Problem Solving and ability to find creative solutions to data problems
- Strong attention to detail and curiosity about data patterns and anomalies
- Understanding of BofA Products, Policies, Procedures, and Guidelines
- Ability to collaborate effectively within and between cross-functional teams
- Awareness of the US marketplace and interest in major industries, consumer brands and financial transaction trends.
Skills:
- Adaptability
- Attention to Detail
- Business Analytics
- Technical Documentation
- Written Communications
- Agile Practices
- Application Development
- Collaboration
- Data Visualization
- DevOps Practices
- Artificial Intelligence/Machine Learning
- Networking
- Policies, Procedures, and Guidelines Management
- Presentation Skills
- Risk Management
Shift:
1st shift (United States of America)
Hours Per Week:
40
INTRODUCTION
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!
ROLE AND RESPONSIBILITIES
This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.
Responsibilities:
- Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights
- Applies agile practices for project management, solution development, deployment, and maintenance
- Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production
- Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment
- Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
- Mitigates risk by identifying potential issues and developing controls
- Researches the latest advances in the fields of data science and artificial intelligence to support business analytics
Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities.
Overview of Data Science for Technology, Risk and Operations:
Data Science for Technology, Risk, and Operations (DSTRO) enables the Bank's responsible adoption of Artificial Intelligence (AI) through governance, model oversight, model development, and enterprise data engineering. By providing AI and model risk governance, AI-driven solutions, and critical transaction data assets, DSTRO delivers the controls, infrastructure, and insights needed to strengthen risk management, enhance operational effectiveness, and drive enterprise value.
As a Data Scientist I supporting the THOR Data Engineering team and Enterprise AI Catalyst program, you will contribute to the development, enhancement, and maintenance of data, AI, and model solutions that address business needs across the enterprise. Working with senior model owners, developers, users, and cross-functional partners, you will analyze large-scale financial transaction data, investigate data patterns and anomalies, develop and validate value-added attributes, and support solutions throughout the product lifecycle, from ideation and testing through production and retirement.
Using SQL and other analytical and data science tools, you will help deliver scalable, compliant solutions that improve decision-making, streamline processes, and support business applications including revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. You will also identify opportunities to leverage and reuse existing AI technologies, models, data assets, and methodologies to reduce duplication and promote best practices.
The role will support THOR product enhancements, quality assurance, production validation, user analytics, technical documentation, training, and informational presentations. Success requires strong analytical and data science capabilities, attention to detail, intellectual curiosity, and effective relationship and project management skills.
Key Responsibilities:
- Support the development, enhancement, and maintenance of THOR data, AI, and model solutions throughout the product lifecycle.
- Analyze large-scale transaction data using SQL and other analytical tools to identify patterns, anomalies, risks, and opportunities.
- Develop, evaluate, audit, and validate transaction categorizations, value-added attributes, and product enhancements.
- Apply established quality-control, testing, documentation, and post-production validation practices.
- Partner with model owners, developers, users, and business teams to understand requirements and deliver scalable, compliant solutions.
- Identify opportunities to reuse existing AI technologies, models, data assets, and methodologies across the enterprise.
- Support analytical requests, user documentation, training materials, and presentations for the THOR user community.
BASIC QUALIFICATIONS
- Data Analysis
- Data Cleansing
- Data Quality and Validation
- Agile Practices
- Technical Documentation
- Written Communications
- Research and Analytical Methods
- Data management
- Data Visualization
- Presentation Skills
- Risk Awareness
- Adaptability
- Problem Solving and ability to find creative solutions to data problems
- Strong attention to detail and curiosity about data patterns and anomalies
- Understanding of BofA Products, Policies, Procedures, and Guidelines
- Ability to collaborate effectively within and between cross-functional teams
- Awareness of the US marketplace and interest in major industries, consumer brands and financial transaction trends.
Skills:
- Adaptability
- Attention to Detail
- Business Analytics
- Technical Documentation
- Written Communications
- Agile Practices
- Application Development
- Collaboration
- Data Visualization
- DevOps Practices
- Artificial Intelligence/Machine Learning
- Networking
- Policies, Procedures, and Guidelines Management
- Presentation Skills
- Risk Management
Shift:
1st shift (United States of America)
Hours Per Week:
40
Data Scientist Job Roles in North Carolina
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Search Data Scientist Jobs in North CarolinaData Scientist Jobs in North Carolina: Frequently Asked Questions
Which companies in North Carolina sponsor visas for data scientists?
SAS Institute in Cary, IBM and Lenovo in the Research Triangle, and pharmaceutical companies like Biogen and Novo Nordisk in Durham have established track records of sponsoring H-1B visas for data scientists. Bank of America and Wells Fargo in Charlotte also regularly file H-1B petitions for quantitative and data roles. DOL LCA disclosure data confirms filings from all of these employers for data science positions.
Which visa types are most common for data scientist roles in North Carolina?
The H-1B is the most common visa for data scientists in North Carolina, as the role consistently qualifies as a specialty occupation requiring at least a bachelor's degree in a relevant field like statistics, computer science, or mathematics. Candidates already holding OPT or STEM OPT through universities such as NC State, Duke, or UNC can work while their employer initiates sponsorship. The O-1A is an option for those with exceptional research credentials.
Which cities in North Carolina have the most data scientist visa sponsorship jobs?
The Research Triangle area, covering Raleigh, Durham, and Chapel Hill, accounts for the majority of data scientist sponsorship activity in the state. The presence of NC State, Duke, and UNC fuels a strong pipeline of technical talent and draws employers who sponsor visas. Charlotte is the secondary hub, particularly for data scientists in financial services and healthcare analytics at companies like Atrium Health.
How to find data scientist visa sponsorship jobs in North Carolina?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search data scientist roles in North Carolina without sifting through positions that don't offer sponsorship. The platform surfaces roles from employers who have active sponsorship histories in the state, including companies in the Research Triangle and Charlotte. Filtering by role and state on Migrate Mate gives you a focused list relevant to your situation.
Are there any North Carolina-specific factors data scientists should know about visa sponsorship?
North Carolina's Research Triangle Park concentration means many sponsoring employers are in life sciences, enterprise software, and advanced manufacturing, sectors where data science roles are well-established and sponsorship is relatively normalized. Employers in these industries are familiar with H-1B processes. NC State and Duke also operate strong OPT-to-sponsorship pipelines, so local hiring managers are accustomed to working with international candidates on work authorization transitions.
What is the prevailing wage for sponsored data scientist jobs in North Carolina?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.