Statistical Data Analyst Jobs in Texas (NOW HIRING)

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About Texas A&M AgriLife

Texas A&M AgriLife is comprised of the following Texas A&M University System members:

• Texas A&M AgriLife Extension Service

• Texas A&M AgriLife Research

• College of Agriculture and Life Sciences at Texas A&M University

• Texas A&M Forest Service

• Texas A&M Veterinary Medical Diagnostic Laboratory

As the nation's largest most comprehensive agriculture program, Texas A&M AgriLife brings together a college and four state agencies focused on agriculture and life sciences within The Texas A&M University System. With over 5,000 employees and a presence in every county across the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service.

Click here to learn more about joining AgriLife!

Position Information

Job Summary:

The Lead Data Analyst, under general direction, serves as a technical lead on complex data projects. Provides technical oversight for the application of and compliance with technical standards. Completes reports and summaries for management and users including project status reports, problem reports, and progress summaries.

Responsibilities:

• Provide leadership and strategic direction for data analysis activities across a portfolio of public health and nutrition research projects, ensuring alignment with organizational and research goals.

• Supervise, mentor, and support data analysts and junior statisticians; delegate tasks, facilitate professional development, and provide technical guidance and quality assurance.

• Oversee the design, implementation, and continual optimization of data analysis workflows, ensuring best practices are established and maintained across projects.

• Review and document data structures to support both current and future research objectives at the program and institutional level.

• Lead the development and application of advanced statistical models and methodologies, including but not limited to: multilevel modeling, mixed models for clustered randomized trials, longitudinal data analysis, and other advanced statistical techniques for complex datasets.

• Oversee the design and execution of statistical analysis plans, including power and sample size calculations, for diverse study designs (e.g., randomized controlled trials, community-randomized trials, longitudinal cohorts) and ensure these meet funding requirements and research objectives.

• Supervise the establishment, maintenance, and improvement of data collection systems; direct data collection and quality assurance activities, including programming forms, monitoring data integrity, and developing data cleaning procedures.

• Coordinate acquisition, cleaning, merging, and management of data from multiple secondary sources (local, state, and national databases) and ensure robust data governance and compliance with relevant privacy and security policies.

• Develop quality control assessments to identify and resolve data issues, implement process improvements, and train team members on best practices in data management and cleaning.

• Oversee and ensure the quality of documentation for data workflows, cleaning, and analysis procedures, and ensure reproducibility and transparency across all stages of the analytic process.

• Prepare or review reports, manuscripts, presentations, and visualizations of analytic findings for internal and external use; ensure clarity, accuracy, and suitability for various audiences.

• Collaborate with principal investigators, multidisciplinary research teams, and external partners (including funding agencies and data stewards) to interpret findings, advise on data strategy, and translate results into actionable insights.

• Lead the development of statistical and analytic sections of grant proposals, supporting funding initiatives and program growth.

• Participate in strategic planning for the data analytics function and represent the data analysis team in broader organizational initiatives.

• Performs other duties as assigned.

Required Qualifications:

• Bachelor's degree in a relevant field (e.g., epidemiology, public health, biostatistics, nutrition, statistics, clinical research) or equivalent combination of education and experience.

• At least 6 years of professional experience in data collection and analysis, including direct experience with statistical modeling and management of research datasets.

• Proficiency in statistical programming languages (e.g., R, SPSS, Stata, SAS), data visualization tools (e.g., Tableau, Power BI), and database applications.

• Demonstrated experience leading the preparation of research manuscripts and securing grant funding.

• Excellent verbal and written communication skills with ability to effectively communicate with faculty and staff.

• Detail oriented and ability to organize tasks and prioritize work with minimal supervision.

• Ability to multi-task and work cooperatively with others.

Preferred Qualifications

• Master's degree or Ph.D. in nutrition epidemiology or related field (e.g., public health, nutrition, statistics, or relevant education and experience meeting job expectations).

• At least one year of related experience.

• Experience working with and accessing local, state and national data sets (e.g., Texas health data, NHANES, WHI, Framingham Heart Study, etc.).

• Experience developing valid, reliable composite scoring and screening instruments (e.g., Life's Simple 7; dietary screeners; etc.).

• Knowledge and understanding of the mission and role of the Land Grant University System, including community-campus partnership and the Extension system.

What You Need to Know

Salary: Compensation is commensurate with the candidate's qualifications.

Flexible Work Arrangements: Flexible work schedules and remote work options may be available for this position, depending on the nature of the role and employee eligibility, in accordance with AgriLife Alternate Work Location Procedures.

Important Notice Regarding H1-B Sponsorship: Your employment at Texas A&M AgriLife may require nonimmigrant sponsorship. A Presidential proclamation issued on September 19, 2025, imposes a $100,000 fee on new H-1B petitions filed after September 21, 2025. Texas A&M AgriLife will NOT pay this fee. If the fee is imposed on your petition, this offer of employment will be revoked. If actions taken during your employment result in the imposition of this fee, your employment will be terminated. To the extent that this statement conflicts with any applicable System or member Policy, Regulation, or Rule, this statement will control. We recommend that you consult with your private immigration counsel at your own expense regarding potential implications.

In addition, on January 27, 2026, Texas Governor Abbott issued a moratorium on the filing of any new H-1B unless approved by the Texas Workforce Commission. Accordingly, if you will now or in the future require sponsorship for employment visa status this moratorium may affect our ability to employ you should you be selected as the final candidate.

Benefits and Leave:

• Health, dental, vision, life and long-term disability insurance (AgriLife contributes to premiums)

• 12-15 annual paid holidays

• Up to 8 hours/month sick leave and at least 8 hours/month vacation

• Automatic enrollment in the Teacher Retirement System of Texas

• Employee Wellness Initiative

• Access to ongoing professional development and training through Aspire, LinkedIn Learning, and internally developed programs

How to Apply

Applications must include all job application data or a complete resume. Incomplete applications may be rejected. Applicants are encouraged to upload a resume or use LinkedIn to prepopulate application fields.

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution's verification of credentials and/or other information required by the institution's procedures, including the completion of the criminal history check.

Equal Opportunity/Veterans/Disability Employer.