Data Science Analyst Visa Sponsorship Jobs in Texas
Texas is one of the top states for data science analyst visa sponsorship, driven by major tech and energy employers in Austin, Dallas, and Houston. Companies like Dell, AT&T, ExxonMobil, and a growing wave of fintech and healthtech firms regularly sponsor H-1B visa and other work visas for qualified data science analysts.
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Get Access To All JobsJob Posting Title:
Senior Data Science Analyst
Hiring Department:
Dell Medical School
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt from FLSA
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue
Location:
AUSTIN, TX
Job Details:
Purpose
The Senior Data Science Analyst is a senior-level expert responsible for leading enterprise-wide data science initiatives that advance clinical care, operational efficiency, and innovation. Reporting to the Chief Data Officer (CDO) or other departmental leader, this role designs and deploys complex statistical and machine learning models, oversees data architecture improvements, and serves as a trusted advisor to organizational leadership. The Senior Data Science Analyst mentors data science staff, guides strategic analytics decisions, and leads the development of advanced data capabilities across the institution.
Responsibilities
Strategic Data Science and Advanced Modeling
- Leads the development of advanced ML and AI models, including deep learning and natural language processing.
- Oversees the design of analytical frameworks for organization-wide initiatives.
- Interprets findings for executive and governance audiences.
- Implements scalable model architectures and optimization strategies.
- Advises leadership on risks, opportunities, and emerging technologies.
Data Architecture, Integration, and Standards
- Leads the integration of heterogeneous data sources across the enterprise.
- Designs data architectures supporting advanced modeling and analytics.
- Develops and enforces data standards, quality measures, and governance.
- Creates robust data models for research, predictive analytics, and operational use.
- Partners with IT to optimize cloud infrastructure and MLOps solutions.
Data Visualization
- Creates enterprise-level dashboards, scorecards, and reporting methodologies.
- Standardizes KPIs across clinical and operational domains.
- Leads automation of recurring analytics and model-driven insights.
Stakeholder Leadership and Strategic Consultation
- Advises senior executives, clinical leaders, and program directors.
- Leads requirements workshops and data strategy sessions.
- Builds consensus on model adoption, data definitions, and governance.
- Represents the analytics program at committees and external forums.
Mentorship, Innovation, and Documentation
- Mentors junior and intermediate analysts in advanced analytics techniques.
- Documents analytical frameworks, data sources, and methodological decisions.
- Leads pilots of emerging AI/ML tools, including synthetic data and automation.
- Contributes to research collaborations, publications, and scholarly activity.
MARGINAL OR PERIODIC FUNCTIONS:
- Conducts periodic audits of data quality and governance standards.
- Evaluates emerging AI/ML tools through short pilots and reports findings.
- Facilitates executive briefings on strategic analytics initiatives.
- Adheres to internal controls and reporting structure.
- Performs related duties as required.
KNOWLEDGE/SKILLS/ABILITIES
Strategic Decision Making and Agility
- Demonstrates strong strategic thinking and has the ability to navigate ambiguous environments.
- Connects analytics roadmap to institutional goals and future capabilities.
- Frames enterprise analytics choices with clear criteria and risk/benefit analysis.
Functional/Technical Skills
- Exhibits expertise in ML, AI, and advanced statistical modeling.
- Selects and implements appropriate ML architectures aligned to problem constraints.
- Designs robust data models and pipelines with reproducibility and monitoring.
Problem Solving
- Maintains a continuous learning and innovation mindset.
- Triages model performance anomalies with root cause analysis and corrective actions.
- Integrates different data sources to address complex, multi-factor questions.
Organizational Savvy
- Provides leadership in cross-functional teams and enterprise initiatives.
- Builds cross-functional alignment on definitions and KPIs.
- Navigates governance bodies to advance responsible AI/ML adoption.
Executive Communication
- Communicates at a high level with messaging tailored to executive audiences.
- Crafts executive level narratives linking insights to operational decisions.
- Builds dashboards and scorecards that reveal trends and actionable thresholds.
Required Qualifications
Requires a Master's Degree in Data Science, Engineering, Statistics, Computer Science, or a related analytical/quantitative field with at least 5 year(s) of experience in advanced analytics or data science.
- Expertise in cloud analytics environments and ML frameworks.
- Experience with healthcare data standards (OMOP, FHIR, DICOM).
- Skilled in large-scale data processing, modeling, and architecture design.
Preferred Qualifications
Doctorate in Engineering, Mathematics, Computer Science, Health Science, Data Science, Statistics, or a related analytical/quantitative field with at least 3 year(s) of experience in a complex healthcare setting.
- Published research or presentations at professional conferences.
- Demonstrated experience in ETL, automation, and at least one cloud environment.
- Experience with clinical informatics data exchange standards and platforms is also desirable.
Relevant education and experience may be substituted as appropriate.
Salary Range
$101,500+ depending on qualifications
Working Environment/Equipment
- Standard office equipment
- Repetitive use of a keyboard
- May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.
Required Materials
- Resume/CV
- 3 work references with their contact information; at least one reference should be from a supervisor
- Letter of interest
Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
- E-Verify Poster (English and Spanish) [PDF]
- Right to Work Poster (English) [PDF]
- Right to Work Poster (Spanish) [PDF]
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified as a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
Job Posting Title:
Senior Data Science Analyst
Hiring Department:
Dell Medical School
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt from FLSA
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue
Location:
AUSTIN, TX
Job Details:
Purpose
The Senior Data Science Analyst is a senior-level expert responsible for leading enterprise-wide data science initiatives that advance clinical care, operational efficiency, and innovation. Reporting to the Chief Data Officer (CDO) or other departmental leader, this role designs and deploys complex statistical and machine learning models, oversees data architecture improvements, and serves as a trusted advisor to organizational leadership. The Senior Data Science Analyst mentors data science staff, guides strategic analytics decisions, and leads the development of advanced data capabilities across the institution.
Responsibilities
Strategic Data Science and Advanced Modeling
- Leads the development of advanced ML and AI models, including deep learning and natural language processing.
- Oversees the design of analytical frameworks for organization-wide initiatives.
- Interprets findings for executive and governance audiences.
- Implements scalable model architectures and optimization strategies.
- Advises leadership on risks, opportunities, and emerging technologies.
Data Architecture, Integration, and Standards
- Leads the integration of heterogeneous data sources across the enterprise.
- Designs data architectures supporting advanced modeling and analytics.
- Develops and enforces data standards, quality measures, and governance.
- Creates robust data models for research, predictive analytics, and operational use.
- Partners with IT to optimize cloud infrastructure and MLOps solutions.
Data Visualization
- Creates enterprise-level dashboards, scorecards, and reporting methodologies.
- Standardizes KPIs across clinical and operational domains.
- Leads automation of recurring analytics and model-driven insights.
Stakeholder Leadership and Strategic Consultation
- Advises senior executives, clinical leaders, and program directors.
- Leads requirements workshops and data strategy sessions.
- Builds consensus on model adoption, data definitions, and governance.
- Represents the analytics program at committees and external forums.
Mentorship, Innovation, and Documentation
- Mentors junior and intermediate analysts in advanced analytics techniques.
- Documents analytical frameworks, data sources, and methodological decisions.
- Leads pilots of emerging AI/ML tools, including synthetic data and automation.
- Contributes to research collaborations, publications, and scholarly activity.
MARGINAL OR PERIODIC FUNCTIONS:
- Conducts periodic audits of data quality and governance standards.
- Evaluates emerging AI/ML tools through short pilots and reports findings.
- Facilitates executive briefings on strategic analytics initiatives.
- Adheres to internal controls and reporting structure.
- Performs related duties as required.
KNOWLEDGE/SKILLS/ABILITIES
Strategic Decision Making and Agility
- Demonstrates strong strategic thinking and has the ability to navigate ambiguous environments.
- Connects analytics roadmap to institutional goals and future capabilities.
- Frames enterprise analytics choices with clear criteria and risk/benefit analysis.
Functional/Technical Skills
- Exhibits expertise in ML, AI, and advanced statistical modeling.
- Selects and implements appropriate ML architectures aligned to problem constraints.
- Designs robust data models and pipelines with reproducibility and monitoring.
Problem Solving
- Maintains a continuous learning and innovation mindset.
- Triages model performance anomalies with root cause analysis and corrective actions.
- Integrates different data sources to address complex, multi-factor questions.
Organizational Savvy
- Provides leadership in cross-functional teams and enterprise initiatives.
- Builds cross-functional alignment on definitions and KPIs.
- Navigates governance bodies to advance responsible AI/ML adoption.
Executive Communication
- Communicates at a high level with messaging tailored to executive audiences.
- Crafts executive level narratives linking insights to operational decisions.
- Builds dashboards and scorecards that reveal trends and actionable thresholds.
Required Qualifications
Requires a Master's Degree in Data Science, Engineering, Statistics, Computer Science, or a related analytical/quantitative field with at least 5 year(s) of experience in advanced analytics or data science.
- Expertise in cloud analytics environments and ML frameworks.
- Experience with healthcare data standards (OMOP, FHIR, DICOM).
- Skilled in large-scale data processing, modeling, and architecture design.
Preferred Qualifications
Doctorate in Engineering, Mathematics, Computer Science, Health Science, Data Science, Statistics, or a related analytical/quantitative field with at least 3 year(s) of experience in a complex healthcare setting.
- Published research or presentations at professional conferences.
- Demonstrated experience in ETL, automation, and at least one cloud environment.
- Experience with clinical informatics data exchange standards and platforms is also desirable.
Relevant education and experience may be substituted as appropriate.
Salary Range
$101,500+ depending on qualifications
Working Environment/Equipment
- Standard office equipment
- Repetitive use of a keyboard
- May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.
Required Materials
- Resume/CV
- 3 work references with their contact information; at least one reference should be from a supervisor
- Letter of interest
Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
- E-Verify Poster (English and Spanish) [PDF]
- Right to Work Poster (English) [PDF]
- Right to Work Poster (Spanish) [PDF]
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified as a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
Data Science Analyst Job Roles in Texas
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Search Data Science Analyst Jobs in TexasData Science Analyst Jobs in Texas: Frequently Asked Questions
Which companies sponsor visas for data science analysts in Texas?
Texas has a broad range of employers with documented H-1B sponsorship histories for data science roles. In Austin, Dell Technologies, Apple, and Oracle are active sponsors. Dallas-based AT&T, American Airlines, and Citi have filed LCAs for data analyst and data science positions. In Houston, ExxonMobil, Schlumberger, and MD Anderson Cancer Center are among the larger sponsors.
Which visa types are most common for data science analyst roles in Texas?
The H-1B is the most common visa for data science analyst positions in Texas, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in a relevant field like statistics, computer science, or mathematics. Some candidates also enter on an F-1 OPT or STEM OPT extension before employer-sponsored H-1B filing. TN visa status is available for Canadian and Mexican nationals in qualifying analytical roles.
Which cities in Texas have the most data science analyst sponsorship jobs?
Austin leads in data science analyst sponsorship driven by its concentration of tech companies and startups. Dallas-Fort Worth is close behind, with strong demand across financial services, telecom, and healthcare sectors. Houston is the primary hub for energy sector data roles, with significant activity in oil and gas analytics. San Antonio has a smaller but growing market tied to cybersecurity and defense contractors.
How to find data science analyst visa sponsorship jobs in Texas?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to find data science analyst roles in Texas where employers are open to sponsoring. You can filter by state and role to surface positions at companies with an established sponsorship history in Texas, which is especially useful given how much the market varies across Austin, Dallas, and Houston.
Are there any Texas-specific considerations for data science analysts seeking visa sponsorship?
Texas has no state income tax, which affects prevailing wage calculations since the Department of Labor benchmarks wages to local market rates. Austin's rapid tech growth has pushed local wage levels upward, so employers sponsoring H-1B petitions in Austin must meet those higher prevailing wage thresholds. University pipelines from UT Austin and Texas A&M also produce strong local talent competition, which can influence how selectively employers pursue international sponsorship.
What is the prevailing wage for sponsored data science analyst jobs in Texas?
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.