Department: Obstetrics & Gynecology
Responsible for all aspects of research projects and research facilities. Plans and conducts clinical and non-clinical research; facilitates and monitors daily activities of clinical trials or research projects. Directs engineering and technical support activities to develop and maintain tools and computational methods needed to gather and analyze data.
Conducts data investigation, including data wrangling, cleaning, sampling, management, exploratory analysis, regression and classification, prediction, and data communication. Implements foundational concepts of data computation, such as data structure, algorithms, parallel computing, simulation, and analysis. Utilizes knowledge in game theory, statistical quality control, exponential smoothing, seasonally adjusted trend analysis, or data visualization to gain insights, develop new strategies, and cultivate actionable business intelligence in diverse career tracks across the University.
P3: Requires in-depth knowledge and experience. Uses best practices and knowledge of internal or external University issues to improve products or services. Solves complex problems; takes a new perspective using existing solutions. Works independently, receives minimal guidance. Acts as a resource for colleagues with less experience.
Responsibilities
The job uses best practices and knowledge of data manipulation, statistical applications, programming, analysis and modeling in order to implement projects related to the University’s various internal data systems as well as from external sources. The job is responsible for managing operational protocols.
1) Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets., 2) Guides staff or faculty members in defining the project and applies principals of data science in manipulation, statistical applications, programming, analysis and modeling., 3) Calibrates data between large and complex research and administrative datasets. Guides and may set the operational protocols for collecting and analyzing information from the University’s various internal data systems as well as from external sources., 4) Designs and evaluates statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Partners with other campus teams to assist faculty with data science related needs., 5) Performs other related work as needed.
Unit-specific Responsibilities
1) Perform significant leadership and creative role in the design, development and execution of quantitative studies using observational, quasi-experimental, experimental and simulation designs as appropriate.
2) Manage and develop a team of masters and more junior-level analysts (biostatistics, informatics, public health, MD-trained analysts) and trainees, including providing support, mentorship and duplicating analyses
3) Lead the writing of the study design and analytic components of proposals, manuscripts and other dissemination materials. Prepare tables and figures for manuscripts, abstracts, and other scientific publications, contributing as author or co-author
4) Oversee development, management and integrity of all research databases, including maintaining and documenting source code for reproducibility of research.
5) Oversee and conduct preparation of datasets for analysis
6) Apply high-level research and writing skills in combination with data analysis skills to ensure timely and effective dissemination of study findings.
7) Identify appropriate statistical methods to address research hypotheses and conduct statistical analyses accordingly. Provide statistical analysis and data management for multiple NIH and other funded projects, including randomized controlled trials, longitudinal intervention studies, network studies of information-based and clinical interventions
8) Participate in regular meetings to discuss proposed analyses, share code and analytic approaches, and discuss data and/or methodological challenges as they arise.
Unit-preferred Competencies
1) Demonstrated ability in effective management and training of analysts
2) Demonstrated success in development and writing of federal (especially NIH) and other funding proposals
3) Demonstrated skills using analytic software including STATA or the equivalent required; ArcGIS preferred; social network, systems science, machine learning, predictive analytics experience a plus
4) Proficiency with Microsoft applications, including but not limited to Outlook, Excel, Access and Word
5) Ability to adhere to protocols for maintaining confidentiality of protected health information, and work with sensitive information
6) Meticulous attention to detail and excellent organizational skills.
7) Ability to work on multiple projects simultaneously, set priorities, and meet deadlines.
8) Excellent interpersonal skills and the ability to work both independently and as part of a team.
9) Demonstrated written and verbal communication skills, including ability to communicate results from complex statistical analyses to a lay audience.
10) Flexibility, creativity, and problem solving skills.
11) Ability to collaborate with colleagues from diverse academic and professional backgrounds.
12) Demonstrated effective leadership skills and ability to manage new analysts or students
For more information and to apply, click HERE.
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