Data Science Engineer Visa Sponsorship Jobs in Texas
Texas is one of the most active states for data science engineer visa sponsorship, driven by technology corridors in Austin, Dallas, and Houston. Major employers include Dell Technologies, AT&T, ExxonMobil, and a growing number of AI-focused startups and financial services firms. The state's lack of income tax also makes it a competitive hiring market for internationally recruited engineering talent.
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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 Engineer Job Roles in Texas
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Search Data Science Engineer Jobs in TexasData Science Engineer Jobs in Texas: Frequently Asked Questions
Which companies sponsor visas for data science engineers in Texas?
Large technology and enterprise firms are the most consistent sponsors for data science engineers in Texas. Companies like Dell Technologies, AT&T, Amazon (Austin fulfillment and tech operations), ExxonMobil, and Lockheed Martin have filed significant numbers of H-1B visa petitions for data-related engineering roles. Texas-based fintech companies and healthcare analytics firms in the Dallas-Fort Worth corridor are also active sponsors, particularly for roles requiring machine learning and statistical modeling expertise.
Which visa types are most common for data science engineer roles in Texas?
The H-1B is the most common visa category for data science engineers in Texas, given that the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, statistics, or a related field. Candidates with advanced degrees may also enter through the H-1B master's cap. Those with extraordinary ability or significant research backgrounds sometimes pursue the O-1A. Australian citizens may qualify for the E-3 visa as an alternative to the H-1B.
Which cities in Texas have the most data science engineer sponsorship jobs?
Austin leads the state for data science engineer sponsorship activity, reflecting its concentration of technology companies and startups. Dallas-Fort Worth is a close second, driven by large corporate headquarters in finance, telecom, and healthcare. Houston contributes meaningful volume through energy sector employers like ExxonMobil and Chevron Phillips, which have expanded their data science functions significantly. San Antonio has a smaller but growing presence, particularly through cybersecurity and defense contractors.
How to find data science engineer visa sponsorship jobs in Texas?
Migrate Mate is built specifically for international candidates searching for visa sponsorship roles, including data science engineer positions in Texas. You can filter by state and role type to surface employers who have a documented history of sponsoring work visas in this field. Because Migrate Mate focuses exclusively on sponsorship-verified listings, it removes the friction of manually researching which Texas employers are open to international candidates.
Are there any Texas-specific considerations for data science engineers seeking visa sponsorship?
Texas has no state income tax, which affects prevailing wage comparisons since employers still must meet Department of Labor wage requirements for the specific metropolitan area. Austin and Dallas have distinct prevailing wage levels that differ from each other, so the same role title can carry different compliance thresholds depending on worksite location. The University of Texas system and Texas A&M also generate a consistent pipeline of OPT-eligible candidates, meaning many Texas employers already have established processes for sponsoring international data science hires.
What is the prevailing wage for sponsored data science engineer 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.