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Statistical Learning Jobs in Texas (NOW HIRING)

Model Development and Deployment Oversee the design, development, and validation of statistical ... Foster a culture of innovation, continuous learning, and collaboration while ensuring alignment ...

New

Model Development and Deployment Oversee the design, development, and validation of statistical ... Foster a culture of innovation, continuous learning, and collaboration while ensuring alignment ...

New

Fraud Risk Analytics Manager

Irving, TX · Hybrid

$106K - $130K/yr

Solid foundation in data science and statistical learning , including: * Classification and regression techniques * Feature engineering * Model evaluation and performance monitoring Preferred ...

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... learning/natural language processing techniques and rigorous ... statistical analysis Utilize LLMs and Generative AI to provide software automation capability ...

Statistics Tutor

Lubbock, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Statistics tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Statistics Tutor

Arlington, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Statistics tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Fraud Risk Analytics Manager

Irving, TX · Hybrid

$106K - $130K/yr

Solid foundation in data science and statistical learning , including: * Classification and regression techniques * Feature engineering * Model evaluation and performance monitoring Preferred ...

Statistics Tutor

San Marcos, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Statistics tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

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Statistical Learning information

What are the key skills and qualifications needed to thrive as a statistical learning specialist?

To thrive as a Statistical Learning Specialist, you need a strong background in statistics, probability, and machine learning, typically supported by an advanced degree in statistics, mathematics, computer science, or a related field. Expertise with programming languages such as Python or R, experience with statistical software (e.g., SAS, MATLAB), and familiarity with data analysis libraries are essential. Critical thinking, problem-solving, and effective communication skills help translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful patterns from data and driving data-informed decision-making.

How do professionals in statistical learning typically collaborate with data scientists and domain experts on projects?

Professionals in statistical learning often work closely with data scientists and domain experts to ensure that the models they develop are both statistically sound and practically relevant. Collaboration usually involves joint problem definition, sharing data insights, and iterative feedback on model performance. Statistical learning experts contribute their knowledge of algorithms and statistical methods, while data scientists handle data pre-processing and engineering, and domain experts provide context to interpret results. This multidisciplinary teamwork helps ensure that solutions are robust and actionable for stakeholders.

What is the difference between Statistical Learning vs Data Analyst?

AspectStatistical LearningData Analyst
Required CredentialsDegree in Statistics, Data Science, or related fieldsDegree in Statistics, Data Science, Business, or related fields
Work EnvironmentResearch, academia, tech companies, data science teamsBusiness, marketing, finance, healthcare organizations
Employer & Industry UsageTech firms, research institutions, startupsCorporations, consulting firms, government agencies
Common Search & ComparisonStatistical Learning vs Data Analyst

Statistical Learning focuses on developing models and algorithms to understand data patterns, often requiring advanced statistical and programming skills. Data Analysts interpret data to generate reports and insights, typically emphasizing data visualization and business understanding. While both roles analyze data, Statistical Learning is more research-oriented and technical, whereas Data Analysts focus on practical data interpretation for decision-making.

What will I become if I study statistical learning?

Studying statistical learning can lead to roles such as data scientist, data analyst, machine learning engineer, or statistician. These positions involve analyzing data, building predictive models, and applying statistical methods using tools like R or Python in various industries.

College of Education, Tenure-Track Assistant Professor in Quantitative Methods

The University of Texas at Austin

Austin, TX • On-site

Full-time

Re-posted 20 days ago


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Company rating: 8.3 out of 10

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Job description

Description
The University of Texas at Austin, College of Education
The University of Texas at Austin, Department of Educational Psychology is seeking a faculty member in the area of Quantitative Methods at the Assistant Professor level. The mission of this program area is to offer training in modern statistical and psychometric methods to prepare graduates to advance methodological research and to apply those methods to address educational and social science research questions. The Department of Educational Psychology has robust graduate programs and is currently ranked #9 among Best Educational Psychology Programs by U.S. News & World Report. The broad focus of the department is scholarship related to health and learning throughout the life span. We are committed to an intellectually diverse, welcoming and engaging working and learning environment and are seeking candidates whose research, teaching and service have prepared them to contribute to our commitment to serving students from across Texas, the country, and world, including those who have been historically underrepresented in higher education.
The successful candidate for this position will have strong potential for research excellence focused broadly on quantitative methods. We are particularly interested in scholars pursuing research impact in the following exemplar areas: multilevel modeling, missing data analysis, research design, multivariate analysis, and/or statistical learning. We expect the successful candidate will have potential for securing external grants to support their program of research, at the level necessary to ensure the impact of their work. In addition, the successful candidate will be an excellent mentor and will demonstrate a strong commitment to teaching in one or more of the following areas: multilevel modeling, missing data analysis, research design, multivariate analysis, and Monte Carlo simulation methods.
The College of Education, ranked among the top public colleges of education in the country, has a longstanding commitment to the shared values of equity, excellence, innovation, empowerment, community-focus, and endeavors to bridge research and practice. We view creating a welcoming, engaged campus community as interconnected with academic excellence in the work of our faculty. The college has experienced a rapid expansion of interest in its academic programs over the past five years. More than half of our admitted students identify as Latina/o and more than 30% are first-generation college students. Our students are joined by a diverse and world class faculty who are among the nation's leading experts in their respective fields.
As a leading college of education in Texas and beyond, we are agents of change committed to transforming education and health research, practice, and policy to ensure the thriving of children, families, schools and communities. In our efforts to align our college to address the most pressing challenges in the fields of education and health, we launched a strategic vision known as Reimagine Education (see education.utexas.edu/about/college-leadership/deans-office/reimagine-education). In advancing this effort, we have organized our academic and research aspirations around three Signature Impact Areas: Advancing Equity and Eliminating Disparities in Health and Education, Attending to Place and Context, and Thriving through Transitions.
Qualifications
Candidates must have the following qualifications:
  • Ph.D. in Quantitative Methods, Quantitative Psychology, Statistics, Applied Statistics, or a closely related field earned by August 2024.
  • Potential for scholarly leadership (i.e., refereed publications, extramural funding) in the area(s) of multilevel modeling, missing data analysis, research design, multivariate analysis, and/or statistical learning.
  • High potential for securing extramural research funding.
  • Experience or capacity to teach and mentor undergraduate and graduate students from a wide range of backgrounds and advance the College's mission.

As a venue for research, Texas is home to more than 10% of the nation's K-12 student population, more than half of whom identify as Hispanic. The University of Texas at Austin is the flagship state university of Texas, and one of the few universities in the U.S. that is both a member of the prestigious Association of American Universities and designated as a Hispanic Serving Institution. UT Austin values and supports interdisciplinary research and, with the opening of the Dell Medical School, provides outstanding access to opportunities for collaboration with world-renowned medical faculty. Austin, Texas is an exciting, welcoming, and inclusive city with the reputation as the Live Music Capital of the World.
The position is supported by a competitive start-up package, compensation appropriate to rank and experience, expansive laboratory space, and access to state-of-the-art core facilities. Hiring is contingent upon funding.
Application Instructions
Review of applications will begin October 2, 2023 and will continue until the position is filled. To ensure full consideration, please provide all requested materials by September 30, 2023. Applicants should upload the following items to the Interfolio system:
  • Cover Letter with contact information
  • Full C.V.
  • Research Statement that includes research accomplishments and future research direction.
  • Teaching and Mentoring Statement that describes specific methods used to ensure effective student mentoring and a classroom environment that is welcoming, engaging, and supportive of student learning and success.
  • Up to 3 representative publications
  • A list of 3 references with contact information

UT Austin is an equal opportunity institution that is committed to recruiting, supporting, and fostering a diverse community of outstanding faculty, staff, and students. We encourage qualified applicants from underrepresented communities to apply.
For additional information about the department, see https://education.utexas.edu/departments/educational-psychology/
For questions regarding the application process, please contact Becky Cook (Becky.Cook@austin.utexas.edu). Questions about the positions can be directed to the chair of the search committee: Dr. Hyeon-Ah Kang (hkang@austin.utexas.edu).

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