Job ID: 146938
Job date: 2017-10-19
End Date:
Company : University of Pittsburgh Country : Role : Other
Job date: 2017-10-19
End Date:
Company : University of Pittsburgh Country : Role : Other
Job Description:
The University of Pittsburgh is seeking a Data Analyst for pharmaceutical outcomes and policy studies under the direction of Dr. Walid Gellad in the School of Medicine, Division of General Internal Medicine. The Data Analyst will work with Dr. Gellad to manage large, healthcare datasets, create analytic data files using complex programming techniques to extract and aggregate raw data, conduct statistical analyses, and document programming and results. There will be several research projects ongoing simultaneously, but the primary project will involve the analyses of claims data and electronic health data and machine learning. The analyst will work in collaboration with epidemiologists and data scientists on machine learning analyses, providing the opportunity to learn new skills in this area. The analyst will also assist faculty or fellows with statistical analysis on health care datasets including claims and EHR data under the direction of Dr. Gellad. Additional responsibilities include assisting with preparing methods and results from sections of manuscripts and presentations, assisting with preparing preliminary data and the methods sections of grant proposals, supporting Data Use Agreement (DUA) applications and IRB submissions, tracking of data assets, and helping to ensure compliance with institutional and federal regulations for human subjects research. The incumbent must demonstrate expertise in data management and statistical analyses, specifically with SAS and/or STATA and R. The candidate must be able to work independently and efficiently with a high level of scientific integrity and attention to detail. The candidate must possess excellent interpersonal, problem-solving, and organizational skills. Experience with large healthcare databases such as Medicare, Medicaid, or health systems data is highly desired. Education Required: Master's Minimum Related Experience Level Required: 3-5 years experience Additional Education and/or Experience Essential to the Position: Master’s Degree in biostatistics/statistics, epidemiology, bioinformatics, or managed information system or other areas with a solid training in applied statistics is required. Preference will be given for candidates with experience with data mining and machine learning. Candidate is required to have 3-5 years’ experience working with large administrative or electronic health data, or relevant experience. Must have experience with SAS and/or STATA or R programming and strength in applied statistics including knowledge of distributions, statistical testing, regression, etc. Experience with very large health care and/or medication-related datasets is preferred. Experience with common data science toolkits such as R, Python, MatLab and data presentation software such as Tableau is preferred.
Additional Info:
Child Protection Clearances: The following PA Act 153 clearances and background checks may be required prior to commencement of employment and as a condition of continued employment: PA State Police Criminal Record Check, FBI Criminal Record Check, PA Child Abuse History Clearance.[Click Here to Access the Original Job Post]
The University of Pittsburgh is seeking a Data Analyst for pharmaceutical outcomes and policy studies under the direction of Dr. Walid Gellad in the School of Medicine, Division of General Internal Medicine. The Data Analyst will work with Dr. Gellad to manage large, healthcare datasets, create analytic data files using complex programming techniques to extract and aggregate raw data, conduct statistical analyses, and document programming and results. There will be several research projects ongoing simultaneously, but the primary project will involve the analyses of claims data and electronic health data and machine learning. The analyst will work in collaboration with epidemiologists and data scientists on machine learning analyses, providing the opportunity to learn new skills in this area. The analyst will also assist faculty or fellows with statistical analysis on health care datasets including claims and EHR data under the direction of Dr. Gellad. Additional responsibilities include assisting with preparing methods and results from sections of manuscripts and presentations, assisting with preparing preliminary data and the methods sections of grant proposals, supporting Data Use Agreement (DUA) applications and IRB submissions, tracking of data assets, and helping to ensure compliance with institutional and federal regulations for human subjects research. The incumbent must demonstrate expertise in data management and statistical analyses, specifically with SAS and/or STATA and R. The candidate must be able to work independently and efficiently with a high level of scientific integrity and attention to detail. The candidate must possess excellent interpersonal, problem-solving, and organizational skills. Experience with large healthcare databases such as Medicare, Medicaid, or health systems data is highly desired. Education Required: Master's Minimum Related Experience Level Required: 3-5 years experience Additional Education and/or Experience Essential to the Position: Master’s Degree in biostatistics/statistics, epidemiology, bioinformatics, or managed information system or other areas with a solid training in applied statistics is required. Preference will be given for candidates with experience with data mining and machine learning. Candidate is required to have 3-5 years’ experience working with large administrative or electronic health data, or relevant experience. Must have experience with SAS and/or STATA or R programming and strength in applied statistics including knowledge of distributions, statistical testing, regression, etc. Experience with very large health care and/or medication-related datasets is preferred. Experience with common data science toolkits such as R, Python, MatLab and data presentation software such as Tableau is preferred.
Requeriments :
Skills :
- Data Mining
- Machine Learning
- Programing in Python
- Programming in Matlab
- Programming in R
- Programming in SAS
- Statistics
Areas :
Additional Info:
Child Protection Clearances: The following PA Act 153 clearances and background checks may be required prior to commencement of employment and as a condition of continued employment: PA State Police Criminal Record Check, FBI Criminal Record Check, PA Child Abuse History Clearance.[Click Here to Access the Original Job Post]