University of Texas
Data Scientist, Department of Women's Health, Dell Medical School
University of Texas, Austin, Texas, us, 78716
Data Scientist, Department of Women's Health, Dell Medical SchoolJob Posting Title:
Data Scientist, Department of Women's Health, Dell Medical School
Hiring Department:
Department of Women's Health
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue
Location:
AUSTIN, TX
Job Details:
Purpose
The Data Scientist will support the research projects within the department led by faculty, fellows, and residents. This position will provide support to ensure research projects run smoothly, meet study-specific objectives, and adhere to specified timelines: study design and development, database development and support, data collection and management, data analysis, and publication and presentation development.
Responsibilities
Data Management:
Develops methodologies and databases for collecting data using REDCap, Qualtrics, and other data collection platforms.
Manages data for clinical/non-clinical trials in all stages of study from different sources: collection, extraction, quality control, cleaning, data manipulation, preparation.
Provides insight into current health data architecture and possible solutions to barriers.
Monitors for compliance with federal and state regulations as well as internal and partner requirements (such as IRB approval, Dell Medical School policies) needed to access or share health data.
Serves as an internal resource to faculty, fellows, and residents to answer questions related to data access, data aggregation, and data management.
Works closely with analysts and informatics staff and with external data teams in Dell Medical School’s partner institutions.
Receives, manages, and delivers requested data tasks; works with data requestors to translate data requests into logical queries using standard language and tools.
Statistical Consulting and Study Collaboration:
Collaborates with investigators to develop statistical analysis plans.
Carries out statistical analyses independently/completes statistical responsibilities for more complex projects with supervision.
Performs power and sample size calculations.
Helps to define research questions and translates them into appropriate methodologies and statistical analyses.
Provides feedback about study design, protocols, and feasibility as it relates to given timelines and settings.
Assists with the interpretation of data when applicable.
Assists with the preparation of data for presentations and publications when applicable.
Regularly attends division research meetings, lab meetings, and 1:1 meetings with collaborators inside and outside of the institution.
Other:
Provides insight and feedback to improve department- and school-wide infrastructure and systems when applicable.
Maintains department-wide databases.
Provides mentorship to fellows and residents when applicable.
Other related duties as assigned.
Required QualificationsBachelor's degree in a related field and at least 2 years of experience in data analysis/science or a related field with complementary experience in data-related fields such as data analysis and data management. At least 2 years of experience with biostatistical and epidemiological knowledge for descriptive statistics, data cleaning/validation, clinical data quality assurance, and research design. Proficient in a range of statistical techniques and procedures. Ability to use R and SAS. Ability to perform power and sample size calculations. Experience developing REDCap databases. Ability to work in high-performing and multidisciplinary teams. Strong analytical and problem-solving skills.
Relevant education and experience may be substituted as appropriate.
Preferred QualificationsPhD in a related field or DrPh from an accredited university. Management and analysis of large, complex clinical research trials. Familiarity with Gpower and PASS. Familiarity with SmartSheet, Qualtrics, and other data management programs.
Salary RangeOPEN
Working Conditions
Repetitive use of a keyboard at a workstation.
Required Materials
Resume/CV
3 work references with their contact information; at least one reference should be from a supervisor.
Letter of interest
Important for applicants who are NOT current university employees or contingent workers:
You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current university employees and contingent workers:
As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left-hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled into your application.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.
E-Verify:
The University of Texas at Austin uses E-Verify to check the work authorization of all new hires effective May 2015.
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act).
About UsIn 2024, The University of Texas at Austin was recognized as a 5 Year Champion having placed in the top 10 among Texas employers and top 15 for higher education institutions on Forbes’s list of 500 best large employers five years running.
#J-18808-Ljbffr
Data Scientist, Department of Women's Health, Dell Medical School
Hiring Department:
Department of Women's Health
Position Open To:
All Applicants
Weekly Scheduled Hours:
40
FLSA Status:
Exempt
Earliest Start Date:
Immediately
Position Duration:
Expected to Continue
Location:
AUSTIN, TX
Job Details:
Purpose
The Data Scientist will support the research projects within the department led by faculty, fellows, and residents. This position will provide support to ensure research projects run smoothly, meet study-specific objectives, and adhere to specified timelines: study design and development, database development and support, data collection and management, data analysis, and publication and presentation development.
Responsibilities
Data Management:
Develops methodologies and databases for collecting data using REDCap, Qualtrics, and other data collection platforms.
Manages data for clinical/non-clinical trials in all stages of study from different sources: collection, extraction, quality control, cleaning, data manipulation, preparation.
Provides insight into current health data architecture and possible solutions to barriers.
Monitors for compliance with federal and state regulations as well as internal and partner requirements (such as IRB approval, Dell Medical School policies) needed to access or share health data.
Serves as an internal resource to faculty, fellows, and residents to answer questions related to data access, data aggregation, and data management.
Works closely with analysts and informatics staff and with external data teams in Dell Medical School’s partner institutions.
Receives, manages, and delivers requested data tasks; works with data requestors to translate data requests into logical queries using standard language and tools.
Statistical Consulting and Study Collaboration:
Collaborates with investigators to develop statistical analysis plans.
Carries out statistical analyses independently/completes statistical responsibilities for more complex projects with supervision.
Performs power and sample size calculations.
Helps to define research questions and translates them into appropriate methodologies and statistical analyses.
Provides feedback about study design, protocols, and feasibility as it relates to given timelines and settings.
Assists with the interpretation of data when applicable.
Assists with the preparation of data for presentations and publications when applicable.
Regularly attends division research meetings, lab meetings, and 1:1 meetings with collaborators inside and outside of the institution.
Other:
Provides insight and feedback to improve department- and school-wide infrastructure and systems when applicable.
Maintains department-wide databases.
Provides mentorship to fellows and residents when applicable.
Other related duties as assigned.
Required QualificationsBachelor's degree in a related field and at least 2 years of experience in data analysis/science or a related field with complementary experience in data-related fields such as data analysis and data management. At least 2 years of experience with biostatistical and epidemiological knowledge for descriptive statistics, data cleaning/validation, clinical data quality assurance, and research design. Proficient in a range of statistical techniques and procedures. Ability to use R and SAS. Ability to perform power and sample size calculations. Experience developing REDCap databases. Ability to work in high-performing and multidisciplinary teams. Strong analytical and problem-solving skills.
Relevant education and experience may be substituted as appropriate.
Preferred QualificationsPhD in a related field or DrPh from an accredited university. Management and analysis of large, complex clinical research trials. Familiarity with Gpower and PASS. Familiarity with SmartSheet, Qualtrics, and other data management programs.
Salary RangeOPEN
Working Conditions
Repetitive use of a keyboard at a workstation.
Required Materials
Resume/CV
3 work references with their contact information; at least one reference should be from a supervisor.
Letter of interest
Important for applicants who are NOT current university employees or contingent workers:
You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current university employees and contingent workers:
As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left-hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled into your application.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.
E-Verify:
The University of Texas at Austin uses E-Verify to check the work authorization of all new hires effective May 2015.
Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act).
About UsIn 2024, The University of Texas at Austin was recognized as a 5 Year Champion having placed in the top 10 among Texas employers and top 15 for higher education institutions on Forbes’s list of 500 best large employers five years running.
#J-18808-Ljbffr