Data Analytics Engineer Visa Sponsorship Jobs in South Carolina
Data analytics engineer roles in South Carolina are concentrated in Charlotte-adjacent markets like Rock Hill, the growing tech corridor around Columbia, and financial services hubs in Greenville. Employers including BlueCross BlueShield of South Carolina, Michelin, and Blackbaud regularly hire for data and analytics engineering positions with visa sponsorship.
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Get Access To All JobsINTRODUCTION
The Fraud Data & Technology Analyst drives data-informed decision-making through analytics, reporting, technology support, and rule optimization. This role delivers actionable insights, evaluates fraud trends and program performance, and supports initiatives that strengthen detection, prevention, and mitigation capabilities. Working closely with the Fraud Data & Technology Lead and cross-functional partners, the analyst helps optimize fraud technologies, enhance controls, improve operational effectiveness, and strengthen customer protection.
ROLE AND RESPONSIBILITIES
What You’ll Do:
Reporting & Analytics:
- Build, automate, and maintain fraud KPIs, dashboards, and reports to measure program performance, loss drivers, mitigation outcomes, and emerging fraud trends.
- Analyze fraud data and translate complex findings into actionable insights, recommendations, and strategic reporting for leadership, operations, and frontline teams.
- Conduct performance assessments, cost-benefit analyses, business case development, and industry research to support fraud strategy, risk identification, and continuous improvement initiatives.
Fraud Technology Support:
- Support the administration, maintenance, optimization, and performance of fraud-related applications, platforms, tools, and system enhancements.
- Coordinate and participate in testing, validation, implementation, troubleshooting, issue resolution, and performance monitoring to ensure technology effectiveness and operational reliability.
- Partner with internal technology teams, business stakeholders, and vendors to support fraud technology initiatives while documenting business processes, system functionality, and operational workflows for governance and knowledge sharing.
Rules & Model Management:
- Tune, calibrate, and optimize fraud detection rules, models, and decisioning strategies to improve detection effectiveness while balancing operational efficiency and customer experience.
- Analyze rule and model performance through testing, alert reviews, and performance metrics, recommending enhancements to fraud monitoring strategies and detection controls.
Data Management:
- Ensure the accuracy, integrity, reliability, and quality of data used in fraud reporting, analysis, and decision-making.
- Support data governance initiatives through documentation, maintenance of data dictionaries and reporting methodologies, quality validation, issue identification, and adherence to reporting standards.
Cross-Functional Partnership:
- Collaborate with stakeholders to identify opportunities for process improvements, automation, and enhanced fraud controls.
- Partner with Fraud Operations, Risk, Compliance, IT, and business teams to support fraud mitigation efforts.
- Provide analytical support and subject matter expertise for fraud-related initiatives.
BASIC QUALIFICATIONS
Requirements For Success:
- Bachelor's degree or higher preferred
- 3+ years of experience in fraud analytics, fraud technology or operations, risk management, or a related field.
Required Skills:
- Hands-on experience with fraud and/or banking platforms.
- Experience with data visualization and reporting tools (e.g., Tableau, Power BI, etc.).
- Experience querying and analyzing large datasets using SQL or similar data analysis tools.
- Knowledge of fraud typologies across payments, digital identity, account takeover, and application fraud.
- Strong analytical, problem-solving, and communication skills.
- Demonstrated ability to collaborate effectively with cross-functional teams.
PREFERRED QUALIFICATIONS
Preferred Skills:
- Experience with machine learning concepts or partnering with data science teams.
- Experience creating or maintaining process maps for technical or operational processes.
- Familiarity with APIs, system integrations, or cloud-based data environments.
- Ability to present complex data insights in a clear and concise manner to both technical and non-technical audiences.
CONDITIONS OF EMPLOYMENT
- Must be able to pass a criminal background & credit check.
- This is a full-time, non-remote position that requires schedule flexibility to work evenings and weekends as needed.
- Up to 10% of travel may be required.
FLSA Status: Exempt
COMPENSATION
Pay Range: USD $49,972.00 - USD $76,958.00 /Yr.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state, or local protected class.
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
INTRODUCTION
The Fraud Data & Technology Analyst drives data-informed decision-making through analytics, reporting, technology support, and rule optimization. This role delivers actionable insights, evaluates fraud trends and program performance, and supports initiatives that strengthen detection, prevention, and mitigation capabilities. Working closely with the Fraud Data & Technology Lead and cross-functional partners, the analyst helps optimize fraud technologies, enhance controls, improve operational effectiveness, and strengthen customer protection.
ROLE AND RESPONSIBILITIES
What You’ll Do:
Reporting & Analytics:
- Build, automate, and maintain fraud KPIs, dashboards, and reports to measure program performance, loss drivers, mitigation outcomes, and emerging fraud trends.
- Analyze fraud data and translate complex findings into actionable insights, recommendations, and strategic reporting for leadership, operations, and frontline teams.
- Conduct performance assessments, cost-benefit analyses, business case development, and industry research to support fraud strategy, risk identification, and continuous improvement initiatives.
Fraud Technology Support:
- Support the administration, maintenance, optimization, and performance of fraud-related applications, platforms, tools, and system enhancements.
- Coordinate and participate in testing, validation, implementation, troubleshooting, issue resolution, and performance monitoring to ensure technology effectiveness and operational reliability.
- Partner with internal technology teams, business stakeholders, and vendors to support fraud technology initiatives while documenting business processes, system functionality, and operational workflows for governance and knowledge sharing.
Rules & Model Management:
- Tune, calibrate, and optimize fraud detection rules, models, and decisioning strategies to improve detection effectiveness while balancing operational efficiency and customer experience.
- Analyze rule and model performance through testing, alert reviews, and performance metrics, recommending enhancements to fraud monitoring strategies and detection controls.
Data Management:
- Ensure the accuracy, integrity, reliability, and quality of data used in fraud reporting, analysis, and decision-making.
- Support data governance initiatives through documentation, maintenance of data dictionaries and reporting methodologies, quality validation, issue identification, and adherence to reporting standards.
Cross-Functional Partnership:
- Collaborate with stakeholders to identify opportunities for process improvements, automation, and enhanced fraud controls.
- Partner with Fraud Operations, Risk, Compliance, IT, and business teams to support fraud mitigation efforts.
- Provide analytical support and subject matter expertise for fraud-related initiatives.
BASIC QUALIFICATIONS
Requirements For Success:
- Bachelor's degree or higher preferred
- 3+ years of experience in fraud analytics, fraud technology or operations, risk management, or a related field.
Required Skills:
- Hands-on experience with fraud and/or banking platforms.
- Experience with data visualization and reporting tools (e.g., Tableau, Power BI, etc.).
- Experience querying and analyzing large datasets using SQL or similar data analysis tools.
- Knowledge of fraud typologies across payments, digital identity, account takeover, and application fraud.
- Strong analytical, problem-solving, and communication skills.
- Demonstrated ability to collaborate effectively with cross-functional teams.
PREFERRED QUALIFICATIONS
Preferred Skills:
- Experience with machine learning concepts or partnering with data science teams.
- Experience creating or maintaining process maps for technical or operational processes.
- Familiarity with APIs, system integrations, or cloud-based data environments.
- Ability to present complex data insights in a clear and concise manner to both technical and non-technical audiences.
CONDITIONS OF EMPLOYMENT
- Must be able to pass a criminal background & credit check.
- This is a full-time, non-remote position that requires schedule flexibility to work evenings and weekends as needed.
- Up to 10% of travel may be required.
FLSA Status: Exempt
COMPENSATION
Pay Range: USD $49,972.00 - USD $76,958.00 /Yr.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state, or local protected class.
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Data Analytics Engineer Job Roles in South Carolina
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Search Data Analytics Engineer Jobs in South CarolinaData Analytics Engineer Jobs in South Carolina: Frequently Asked Questions
Which companies sponsor visas for data analytics engineers in South Carolina?
Employers with a documented history of sponsoring H-1B visas for data and analytics roles in South Carolina include BlueCross BlueShield of South Carolina, Blackbaud, Michelin North America, and Benefitfocus. Technology consulting firms and financial services companies operating in the Columbia and Greenville metro areas also appear in Department of Labor LCA disclosure data for analytics engineering positions.
Which visa types are most common for data analytics engineer roles in South Carolina?
The H-1B is the most common visa category for data analytics engineers in South Carolina, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, information systems, or a related field. Applicants already holding L-1B status with a multinational employer, particularly in manufacturing or financial services, may also transition into data engineering roles without entering the H-1B lottery.
Which cities in South Carolina have the most data analytics engineer sponsorship jobs?
Columbia leads the state for data analytics engineering sponsorship activity, driven by state government technology contracts, insurance sector employers, and the University of South Carolina's technology ecosystem. Greenville is a secondary hub, supported by manufacturing-sector analytics demand from companies like Michelin and BMW's nearby operations. Charleston is emerging, particularly in fintech and defense contracting, with growing analytics hiring across both sectors.
How to find data analytics engineer visa sponsorship jobs in South Carolina?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to browse data analytics engineer openings in South Carolina without sorting through roles that don't offer sponsorship. You can filter by state and role type to surface positions from employers who have actively sponsored visas for analytics engineering talent, saving significant time in your search.
Are there any state-specific considerations for data analytics engineers seeking sponsorship in South Carolina?
South Carolina's relatively lower cost of living compared to coastal tech markets affects prevailing wage calculations under the Labor Condition Application, which employers must file before sponsoring an H-1B. The state's university pipeline, including Clemson's computing programs and the University of South Carolina's data science offerings, means employers are accustomed to recruiting internationally trained graduates. Manufacturing-sector roles may require domain knowledge in industrial analytics alongside traditional data engineering skills.
What is the prevailing wage for sponsored data analytics engineer jobs in South 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.