Tenure Track Professor of Data Analytics

Alexandria's academic sector shows growing interest in data analytics education, but tenure track roles remain limited. Candidates should expect a moderate competition level, where expertise in interdisciplinary data analytics and sports analytics can provide a significant advantage against other applicants.

While a Ph.D. is paramount for tenure track data analytics professors in Ohio, additional certifications in data science, analytics software, or advanced statistical methods can enhance candidacy. Regional universities value interdisciplinary credentials that bridge analytics with applied fields like sports analytics.

Candidates should highlight strong proficiency in data analytics methodologies, interdisciplinary research capabilities, and teaching experience in analytics tools, especially within sports analytics. Practical skills in programming, data visualization, and statistical analysis are highly regarded for this academic position.

Advancement typically involves publishing impactful research, securing grants, and contributing to curriculum development. Progression may lead to associate professorships, department leadership, or roles in cross-disciplinary centers focused on data science and analytics education.

At the American Economic Association, the position integrates economic applications with data analytics, offering unique research collaborations and a platform to influence economic analytics education nationally. This role emphasizes interdisciplinary approaches more heavily than typical university appointments.

Yes, the Association encourages faculty to adopt cutting-edge pedagogies, including project-based learning and integration of real-world analytics cases, fostering an environment where professors can blend theory with practical data science applications.

Salaries for tenure track data analytics professors in Alexandria typically range from $70,000 to $95,000 annually, depending on experience and credentials. This range reflects the regional academic market and the specialized nature of interdisciplinary data analytics expertise.

Expect a balance between delivering approximately five courses annually and engaging in active research. Responsibilities also include curriculum development, mentoring students, and collaborating across departments, particularly emphasizing applied data analytics in sports and economics.

Integrating technical analytics content within a liberal arts framework requires tailoring complex data science concepts for diverse student backgrounds, fostering interdisciplinary collaboration, and continuously updating curriculum to reflect fast-evolving analytics tools and applications.