Data Analyst

Oklahoma Medical Research Foundation

Oklahoma City, OK

ID: 7293613 (Ref.No. ej-5796794)
Posted: Newly posted

Job Description


Data Analyst

Overview
Founded in 1946, the Oklahoma Medical Research Foundation (OMRF) is among the nation's oldest, most respected independent, nonprofit biomedical research institutes. OMRF is dedicated to understanding and developing more effective treatments for human diseases, focusing on critical research areas such as Alzheimer's disease, cancer, lupus, Multiple Sclerosis, and cardiovascular disease. OMRF follows an innovative cross-disciplinary approach to medical research and ranks among the nation's leaders in patents per scientist.
Located in Oklahoma City, a city that offers a dynamic and flourishing downtown area, with low cost of living, short commute times and a diversified economy, OMRF has been voted one of the Top Workplaces since the inception of the award. This achievement has been accomplished thanks to OMRF individuals who share a unified understanding that our excellence can only be fully realized with a commitment to diversity, equity, and inclusion. Successful candidates will demonstrate commitment to these values.
Benefits
We offer competitive salaries and comprehensive benefits including, medical, dental, and vision insurance, minimum 8% company retirement contribution, vacation and sick leave, paid holidays, onsite cafe, free onsite fitness center with access to personal trainer, free parking and much more! Relocation assistance available for those located 50 miles outside of Oklahoma City metro and out of state. Learn more about our benefits here.
OMRF is an Equal Opportunity/Affirmative Action/Veterans Employer. All qualified applicants will receive consideration for employment without regard to gender, sexual orientation, gender identity, race, color, national origin, age, religion, disability, veteran status, or any other legally protected characteristic.
Responsibilities
The Montgomery Lab is seeking a Data Analyst/Bioinformatician to support research in sarcoidosis. This role will involve analyzing complex data sets from study participants. This position is ideal for an individual passionate about applying data science to uncover biological mechanisms. Some key responsibilities include:
  • Conduct bioinformatics and biostatistical analyses of high-throughput data related to gene expression, proteomics, and other -omics data.
  • Willing to participate in laboratory experiments as needed.
  • Utilize machine learning approaches, data visualization techniques, and high-content data analysis tools to support the lab's research in vascular integrity, thrombosis, and host-microbiota interactions.
  • Collaborate with basic scientists, clinical researchers, and other data analysts to interpret data, generate reports for publication, and contribute to grant applications.
  • Work both independently and as part of the broader Translational Informatics team, contributing to data management and process improvement initiatives.
    Qualifications
    • Bachelor’s degree in bioinformatics, mathematics, statistics, biostatistics, computer science, MIS, or a related field, plus at least 2 years of relevant experience or a combination of relevant education and experience.• Demonstrated expertise in data analysis, project management, and the ability to communicate findings clearly.• Strong organizational skills, attention to detail, and the ability to manage multiple priorities in a research setting.
    To apply, visit https://careers-omrf.icims.com/jobs/1768/data-analyst/job?in_iframe=1
    OMRF’s excellence can only be fully realized by individuals who share our commitment to diversity, equity and inclusion. Successful candidates will demonstrate commitment to these values. OMRF is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to gender, sexual orientation, gender identity, race, color, national origin, age, religion, disability, veteran status or any other legally protected characteristic.

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