PHD in Statistics and Data Science

Class Profile

Career Outcomes

Median Earnings After Graduation

$1,10,000 / year

FAQs

• What career opportunities are available after completing this PhD?
  
  Graduates are prepared for careers in: Academia (professorships, research faculty) Industry positions in tech, finance, healthcare, government, and consulting Research centers and think tanks focused on statistical and data science applications The program emphasizes skills relevant to both statistics and machine learning, offering numerous career paths.
• What are the tuition fees and funding options?
  
  All admitted students are guaranteed five years of financial support, which often includes a combination of research assistantships, teaching assistantships, and fellowships. These typically cover tuition and provide a stipend for living expenses. More information on exact fees and funding can be found directly through the department
• How do I apply for the PhD in Statistics and Data Science at UT Austin?
  
  Applicants should prepare: Academic transcripts and degree certificates Curriculum Vitae (CV) Statement of purpose/research interests Three letters of recommendation Proof of English proficiency (if required) All application materials should be submitted electronically via the university’s online application portal. Application deadlines for the PhD program are generally in December/January for fall intake. Early submission is advised for funding consideration.
• What are the minimum academic and English language entry requirements?
  
  Applicants must hold a strong undergraduate background in mathematics or a related field. Evidence of prior coursework in linear algebra, advanced calculus, and statistics is often expected. Non-native English speakers must demonstrate proficiency, usually by submitting TOEFL or IELTS scores as required by the Graduate School.
• What is the structure and duration of the PhD in Statistics and Data Science at UT Austin?
  
  The PhD program typically requires approximately five years of full-time study to complete. Students must fulfill core coursework, advanced electives, research credits, qualifying exams, and dissertation work. The curriculum features cutting-edge statistical methodology and the opportunity to work with multiple faculty members on interdisciplinary topics.