Data Science Manager Visa Sponsorship Jobs in Texas
Texas is one of the strongest states for data science manager roles, with major hiring in Austin's tech corridor, Dallas-Fort Worth's financial and telecom sectors, and Houston's energy and healthcare industries. Employers like Dell, AT&T, ExxonMobil, and a growing field of tech startups regularly sponsor H-1B visas for senior data science positions.
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Get Access To All JobsSenior Data Science Analyst (Corporate)
This position is Hybrid working from our Legacy West Support Center located in Plano, Texas.
About Sally Beauty Holdings, Inc.
At SBH, our purpose is to inspire a more colorful, confident, and welcoming world. We are the leader in professional hair color, selling and distributing professional beauty supplies across 11 countries through our Sally Beauty and Beauty Systems Group businesses. Sally Beauty offers products for hair color, hair care, nails, and skin care to retail customers looking for salon quality products at a value price. Beauty Systems Group, branded as Cosmo Prof or Armstrong McCall stores, along with its direct sales consultants, sell professionally branded products intended for use and resale by salons to retail consumers.
About the Role
The Senior Data Science Analyst is a hands-on technical contributor responsible for building predictive models, advanced analytics solutions, and production-ready data products that help Sally Beauty Holdings better understand and activate customer behavior. This role combines data science, machine learning, statistical analysis, and data engineering to drive customer acquisition, retention, engagement, and lifetime value initiatives.
Working at the intersection of advanced analytics and commercial strategy, the Senior Data Science Analyst partners closely with Customer Analytics, CRM, Marketing, Merchandising, and Data Engineering teams to develop scalable models and insights that support hyper-personalized customer experiences. This role owns the end-to-end lifecycle of data science initiatives, including problem definition, feature engineering, model development, validation, deployment, monitoring, and ongoing optimization.
Responsibilities
- Develop, validate, deploy, and monitor machine learning models that support customer acquisition, retention, churn reduction, customer lifetime value (CLV), segmentation, propensity scoring, and next-best-action recommendations.
- Design and implement advanced customer segmentation strategies using behavioral, transactional, demographic, and value-based data.
- Apply statistical and machine learning methodologies including clustering, regression, classification, survival analysis, recommender systems, and market basket analysis to identify business opportunities.
- Conduct exploratory data analysis, feature engineering, model evaluation, and validation to ensure high-quality and statistically sound outcomes.
- Develop customer-focused analytics and predictive assets that support CRM campaigns, loyalty initiatives, and customer lifecycle management strategies.
- Build and maintain scalable customer data pipelines and customer 360 solutions within Databricks using Python, PySpark, and SQL.
- Convert analytical prototypes into production-ready solutions with a focus on scalability, reliability, maintainability, and business impact.
- Implement and maintain MLOps processes including automated model scoring, retraining, performance monitoring, drift detection, and data quality validation.
- Follow software engineering best practices including version control, peer code review, testing, and CI/CD deployment processes.
- Design, execute, and analyze A/B tests and multivariate experiments across digital marketing channels including email, SMS, push notifications, and mobile applications.
- Develop statistically valid test and control audiences to support accurate measurement of campaign effectiveness and incremental business impact.
- Partner with CRM and Marketing teams to optimize customer journeys including onboarding, growth, retention, and reactivation programs.
- Translate complex analytical findings into clear business recommendations for technical and non-technical stakeholders.
- Present insights, forecasts, and recommendations to senior leadership and cross-functional partners.
- Support ad hoc analyses, strategic initiatives, and special projects that advance customer and business objectives.
Knowledge, Skills & Abilities Requirements
- Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Physics, Analytics, or a related quantitative field preferred.
- 4+ years of experience in data science, machine learning, customer analytics, or advanced analytics roles.
- Experience within retail, ecommerce, consumer packaged goods (CPG), loyalty, subscription, or customer-focused industries preferred.
- Advanced proficiency in Python, including pandas, NumPy, scikit-learn, and related data science libraries.
- Advanced proficiency in SQL for data extraction, transformation, and analysis.
- Experience with Databricks, Spark/PySpark, Delta Lake, and cloud-based analytics environments, preferably Microsoft Azure.
- Strong understanding of machine learning techniques including regression, classification, clustering, tree-based models, boosting algorithms, survival analysis, recommender systems, and dimensionality reduction methods.
- Solid foundation in statistics, experimental design, hypothesis testing, confidence intervals, cross-validation, probability, and predictive modeling.
- Experience deploying, monitoring, and maintaining production machine learning solutions using tools such as MLflow or similar frameworks.
- Knowledge of software development best practices including Git, code reviews, testing methodologies, and CI/CD processes.
- Strong proficiency in Microsoft Excel and PowerPoint with the ability to communicate analytical findings through executive-ready presentations.
- Ability to manage multiple priorities and deliver high-quality analytical solutions in a fast-paced environment.
- Exceptional analytical thinking, problem-solving, and business acumen.
Competencies & Attributes
- Passionate Learner – Continuously seeks new knowledge, embraces feedback, and applies learning to improve analytical capabilities, business outcomes, and operational processes.
- Flexible & Agile Adapter – Thrives in evolving environments, navigates ambiguity effectively, and adjusts priorities to meet changing business needs.
- Effective Communicator – Communicates technical concepts, analytical findings, and business recommendations clearly to audiences of varying technical expertise.
- Team Builder – Collaborates effectively across functions, shares knowledge, and contributes to a culture of inclusion, partnership, and continuous improvement.
- Customer Focused Partner – Uses customer insights and analytics to improve the customer experience, support business decisions, and drive measurable results.
- Strategic Thinker – Connects analytical findings to broader business objectives and identifies scalable, data-driven opportunities for growth.
- Big Picture Thinker – Understands how customer analytics, marketing, merchandising, and technology initiatives work together to drive business performance.
- Results Driver – Demonstrates accountability, prioritizes high-impact work, and consistently delivers quality outcomes that support organizational goals.
- Problem Solver & Decision Maker – Applies data, statistical rigor, and business judgment to solve complex challenges and make informed recommendations.
- Data Innovator – Actively seeks new methodologies, technologies, and analytical approaches to improve predictive capabilities and business performance.
Working Conditions & Physical Requirements
This will be a hybrid role required to be onsite at the corporate office on specified days. The work environment generally involves everyday risks or discomforts which require normal safety precautions typical of such places as offices, meeting and training rooms, retail stores, and residences or commercial vehicles, including the use of standard office equipment and adherence to workplace safety practices. The work area is adequately lit, heated, and ventilated.
The work is sedentary. Typically, the employee may sit comfortably to perform the work. However, there may be occasional walking, standing, bending, and lifting or carrying light office equipment and materials as needed.
Benefits
We offer a competitive salary and outstanding benefits package that includes medical, dental, vision, life insurance, paid vacation and sick days, paid holidays, tuition reimbursement and 401(k) with company match. In addition, associates of SBH may take advantage of our in-house salon with complimentary services and a varied selection of food options at our corporate campus. Also featured at our corporate campus is both a Sally Beauty and CosmoProf Professional onsite store, where associates enjoy a great merchandise discount!
Senior Data Science Analyst (Corporate)
This position is Hybrid working from our Legacy West Support Center located in Plano, Texas.
About Sally Beauty Holdings, Inc.
At SBH, our purpose is to inspire a more colorful, confident, and welcoming world. We are the leader in professional hair color, selling and distributing professional beauty supplies across 11 countries through our Sally Beauty and Beauty Systems Group businesses. Sally Beauty offers products for hair color, hair care, nails, and skin care to retail customers looking for salon quality products at a value price. Beauty Systems Group, branded as Cosmo Prof or Armstrong McCall stores, along with its direct sales consultants, sell professionally branded products intended for use and resale by salons to retail consumers.
About the Role
The Senior Data Science Analyst is a hands-on technical contributor responsible for building predictive models, advanced analytics solutions, and production-ready data products that help Sally Beauty Holdings better understand and activate customer behavior. This role combines data science, machine learning, statistical analysis, and data engineering to drive customer acquisition, retention, engagement, and lifetime value initiatives.
Working at the intersection of advanced analytics and commercial strategy, the Senior Data Science Analyst partners closely with Customer Analytics, CRM, Marketing, Merchandising, and Data Engineering teams to develop scalable models and insights that support hyper-personalized customer experiences. This role owns the end-to-end lifecycle of data science initiatives, including problem definition, feature engineering, model development, validation, deployment, monitoring, and ongoing optimization.
Responsibilities
- Develop, validate, deploy, and monitor machine learning models that support customer acquisition, retention, churn reduction, customer lifetime value (CLV), segmentation, propensity scoring, and next-best-action recommendations.
- Design and implement advanced customer segmentation strategies using behavioral, transactional, demographic, and value-based data.
- Apply statistical and machine learning methodologies including clustering, regression, classification, survival analysis, recommender systems, and market basket analysis to identify business opportunities.
- Conduct exploratory data analysis, feature engineering, model evaluation, and validation to ensure high-quality and statistically sound outcomes.
- Develop customer-focused analytics and predictive assets that support CRM campaigns, loyalty initiatives, and customer lifecycle management strategies.
- Build and maintain scalable customer data pipelines and customer 360 solutions within Databricks using Python, PySpark, and SQL.
- Convert analytical prototypes into production-ready solutions with a focus on scalability, reliability, maintainability, and business impact.
- Implement and maintain MLOps processes including automated model scoring, retraining, performance monitoring, drift detection, and data quality validation.
- Follow software engineering best practices including version control, peer code review, testing, and CI/CD deployment processes.
- Design, execute, and analyze A/B tests and multivariate experiments across digital marketing channels including email, SMS, push notifications, and mobile applications.
- Develop statistically valid test and control audiences to support accurate measurement of campaign effectiveness and incremental business impact.
- Partner with CRM and Marketing teams to optimize customer journeys including onboarding, growth, retention, and reactivation programs.
- Translate complex analytical findings into clear business recommendations for technical and non-technical stakeholders.
- Present insights, forecasts, and recommendations to senior leadership and cross-functional partners.
- Support ad hoc analyses, strategic initiatives, and special projects that advance customer and business objectives.
Knowledge, Skills & Abilities Requirements
- Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Physics, Analytics, or a related quantitative field preferred.
- 4+ years of experience in data science, machine learning, customer analytics, or advanced analytics roles.
- Experience within retail, ecommerce, consumer packaged goods (CPG), loyalty, subscription, or customer-focused industries preferred.
- Advanced proficiency in Python, including pandas, NumPy, scikit-learn, and related data science libraries.
- Advanced proficiency in SQL for data extraction, transformation, and analysis.
- Experience with Databricks, Spark/PySpark, Delta Lake, and cloud-based analytics environments, preferably Microsoft Azure.
- Strong understanding of machine learning techniques including regression, classification, clustering, tree-based models, boosting algorithms, survival analysis, recommender systems, and dimensionality reduction methods.
- Solid foundation in statistics, experimental design, hypothesis testing, confidence intervals, cross-validation, probability, and predictive modeling.
- Experience deploying, monitoring, and maintaining production machine learning solutions using tools such as MLflow or similar frameworks.
- Knowledge of software development best practices including Git, code reviews, testing methodologies, and CI/CD processes.
- Strong proficiency in Microsoft Excel and PowerPoint with the ability to communicate analytical findings through executive-ready presentations.
- Ability to manage multiple priorities and deliver high-quality analytical solutions in a fast-paced environment.
- Exceptional analytical thinking, problem-solving, and business acumen.
Competencies & Attributes
- Passionate Learner – Continuously seeks new knowledge, embraces feedback, and applies learning to improve analytical capabilities, business outcomes, and operational processes.
- Flexible & Agile Adapter – Thrives in evolving environments, navigates ambiguity effectively, and adjusts priorities to meet changing business needs.
- Effective Communicator – Communicates technical concepts, analytical findings, and business recommendations clearly to audiences of varying technical expertise.
- Team Builder – Collaborates effectively across functions, shares knowledge, and contributes to a culture of inclusion, partnership, and continuous improvement.
- Customer Focused Partner – Uses customer insights and analytics to improve the customer experience, support business decisions, and drive measurable results.
- Strategic Thinker – Connects analytical findings to broader business objectives and identifies scalable, data-driven opportunities for growth.
- Big Picture Thinker – Understands how customer analytics, marketing, merchandising, and technology initiatives work together to drive business performance.
- Results Driver – Demonstrates accountability, prioritizes high-impact work, and consistently delivers quality outcomes that support organizational goals.
- Problem Solver & Decision Maker – Applies data, statistical rigor, and business judgment to solve complex challenges and make informed recommendations.
- Data Innovator – Actively seeks new methodologies, technologies, and analytical approaches to improve predictive capabilities and business performance.
Working Conditions & Physical Requirements
This will be a hybrid role required to be onsite at the corporate office on specified days. The work environment generally involves everyday risks or discomforts which require normal safety precautions typical of such places as offices, meeting and training rooms, retail stores, and residences or commercial vehicles, including the use of standard office equipment and adherence to workplace safety practices. The work area is adequately lit, heated, and ventilated.
The work is sedentary. Typically, the employee may sit comfortably to perform the work. However, there may be occasional walking, standing, bending, and lifting or carrying light office equipment and materials as needed.
Benefits
We offer a competitive salary and outstanding benefits package that includes medical, dental, vision, life insurance, paid vacation and sick days, paid holidays, tuition reimbursement and 401(k) with company match. In addition, associates of SBH may take advantage of our in-house salon with complimentary services and a varied selection of food options at our corporate campus. Also featured at our corporate campus is both a Sally Beauty and CosmoProf Professional onsite store, where associates enjoy a great merchandise discount!
Data Science Manager Job Roles in Texas
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Search Data Science Manager Jobs in TexasData Science Manager Jobs in Texas: Frequently Asked Questions
Which companies sponsor visas for data science managers in Texas?
Texas has a wide range of H-1B sponsors for data science manager roles. Technology companies like Dell, IBM, and Oracle have significant operations in Austin and the DFW metroplex. In Houston, energy firms including ExxonMobil and Chevron hire data science leadership. Telecom giants like AT&T and financial institutions headquartered in Dallas also appear consistently in DOL disclosure data as H-1B sponsors for senior data science positions.
Which visa types are most common for data science manager roles in Texas?
The H-1B is by far the most common visa for data science managers in Texas. The role qualifies as a specialty occupation given its requirement for a bachelor's degree or higher in computer science, statistics, or a related field. Candidates already holding L-1A status through multinational employers may also transition into managerial data science roles, and those with extraordinary ability may pursue the O-1A, though that path requires substantial documented achievements.
Which cities in Texas have the most data science manager sponsorship jobs?
Austin leads Texas for data science manager sponsorship activity, driven by a dense concentration of tech companies and fast-growing startups. Dallas-Fort Worth ranks second, with strong demand from financial services, telecom, and enterprise software firms. Houston contributes meaningfully through its energy, healthcare, and logistics sectors. San Antonio has a smaller but growing presence, particularly tied to cybersecurity and defense-adjacent technology employers.
How to find data science manager visa sponsorship jobs in Texas?
Migrate Mate filters job listings specifically for visa sponsorship, making it straightforward to find data science manager roles in Texas without sorting through positions that won't support international candidates. You can search by role and state to see employers actively hiring for data science leadership in Austin, Dallas, Houston, and beyond. Migrate Mate pulls from H-1B sponsorship history, so you're seeing employers with a real track record of sponsoring this type of role.
Are there any Texas-specific factors that affect data science manager sponsorship?
Texas has no state income tax, which affects prevailing wage benchmarking since the DOL calculates wages based on local cost of labor rather than take-home pay. Austin's rapid growth has pushed local prevailing wages upward, meaning employers must meet higher thresholds for LCA certification. Texas also benefits from strong university pipelines through UT Austin, Texas A&M, and Rice University, which means many employers in the state are experienced with international talent and sponsorship processes.
What is the prevailing wage for sponsored data science manager 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.