Data Scientist I, Internal Medicine, Cardiology

Remote Full-time
WHY UT SOUTHWESTERN?
With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report, we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you'll discover a culture of teamwork, professionalism, and a rewarding career!

JOB SUMMARY
Works under specific direction to provide analysis and develops algorithms and software for clinical and/or basic research problems. Impacts data acquisition, management, and analysis in basic, translational, and clinical research, including clinical trials.

This position will support a PI who has ongoing funded research projects involving analyses of complex, high-dimensional, longitudinal data. This work requires high-level expertise in data analysis to successfully implement and complete these projects. The ideal candidate will have a graduate degree in a computational field (statistics, bioinformatics, computer science, etc.) and is someone who can function very independently and under the general direction of the PI, performing high-level, complex research activities. In addition to supporting several large and ongoing grant-funded projects, this person will support the next phase of the Dallas Hearts and Minds Study as it transitions away from a clinic visit and into a manuscript preparation phase. This position will independently create and implement statistical analyses plans to support manuscript publication.

Position expected duties:
• Perform independent statistical analyses focusing on bioinformatic analyses including regression (linear, logistic, etc.) and survival analysis, in epidemiologic cohort studies. The applicant would be responsible for independently performing exploratory analyses and contributing to go/no go decisions for further investigation.
• Develop new and implement existing statistical code to support ongoing research projects in the group. This includes assisting doctoral and post-doctoral research fellows with data analyses. Statistical analyses will primarily be performed in STATA and R, but other software (e.g. Python) may also be used.
• Generate data visualizations to support study analyses. Working with the PI, biostatistical collaborator, and other study staff, determine and generate appropriate data visualizations to support data analyses. It is anticipated that data visualizations will be performed in STATA, R, and other relevant software.
• Collect and maintain data analysis code for study analyses, and documentation detailing analyses performed.
• All other duties, as assigned.

Experience working with healthcare data is preferred. Cardiology experience is not required but would be a bonus.

BENEFITS
UT Southwestern is proud to offer a competitive and comprehensive benefits package to eligible employees. Our benefits are designed to support your overall wellbeing, and include:
• PPO medical plan, available day one at no cost for full-time employee-only coverage
• 100% coverage for preventive healthcare-no copay
• Paid Time Off, available day one
• Retirement Programs through the Teacher Retirement System of Texas (TRS)
• Paid Parental Leave Benefit
• Wellness programs
• Tuition Reimbursement
• Public Service Loan Forgiveness (PSLF) Qualified Employer
• Learn more about these and other UTSW employee benefits!

EXPERIENCE AND EDUCATION
Required
• Education
Master's Degree M.S. in Computer Science, Bioinformatics, (Bio)mathematics, (Bio)statistics, Physics, Electrical Engineering, or related field or
Bachelor's Degree B.S. with demonstrated experience in broadly defined areas of bioinformatics
• Experience
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