IEOR - Designing a More Efficient World

Portfolio Analysis & Training SME at ERPi

View job on Handshake

Employer: ERPi

Expires: 05/31/2020

OverviewERPi is a Service-Disabled Veteran-Owned Small Business, dedicated to values of trust and integrity. Our mission is to deliver professional services as a trusted agent and expert enterprise program management services for Federal clients.ERPi is currently seeking a full-time Portfolio Analysis & Training SME to provide onsite support at our Bethesda, MD site.Background:The goal of the National Heart, Lung, and Blood Institute’s Office of Management Portfolio Analytics Strategy is to help provide National Institutes of Health (NIH) staff with knowledge, analysis support, and tools for analyses to support data driven decision making in the management of its research portfolio. Analyses will support an improved understanding of research on diseases and conditions, cross-agency funding trends, research gaps and overlap, research demographics, research outputs, and areas of scientific and health improvement opportunities upon which NIH should capitalize or in which NIH investment can provide enabling resources (e.g., research initiatives). In addition to developing new tools, this strategy seeks to create a formal structure and process(es) for providing rigorous analyses and review of NIH funding investments, develop and implement analysis training, and serve as a repository of information about how to carry out various types of Portfolio Analysis. Key categories of Portfolio Analysis include: 1) reporting on portfolio information to internal and external stakeholders; 2) analysis of portfolio information to inform management and strategic planning; and 3) evaluation of research portfolios and programs.Role Description:ERPi is seeking an experienced professional with NIH research portfolio and data analytics experience that can assess and develop the best possible Portfolio Analysis Training to support the evaluation, assessment, and initiative development needs of NHBLI and the Extramural Program Staff. This individual will deliver these trainings to various NIH staff including Extramural Program Staff. The ideal candidate will have a passion for supporting fast-moving and wide-ranging data science oriented projects and initiatives at NIH. The candidate should be innovative and strategic and have a passion for motivating and engaging ERPi team members and client stakeholders. The responsibilities include, but are not limited to:Individual will support the implementation of the OM Portfolio Analytics Strategy to help identify requirements for training, analysis methodologies, and data governance, etc.Individual will develop training to orient staff to available tools and data systems to meet their analysis needs.Individual will provide information on how the data is structured (complex data collection, cleaning processes and the definitions of the data elements), what analyses are possible, and what tools are available through NHLBI and the broader NIH.This individual will develop a list of the type of ad hoc analyses that cannot use automated reporting tools or the dashboard methods. This training will explore with staff what is possible and how it is carried out (challenges, time to completion, available outcomes, etc.). Other topics to be covered:How best to ask the right question(s) to get the desired answer (logic models, basic program evaluation methods, etc.)Demonstrate the collaborative, iterative process for working with an analyst or analysts to carry out the evaluation/assessment which includes discussion of: Types of available data (e.g., data variants, data definitions, data lineage, data quality, etc.).Tools that can support the analysis and their availability.Possible methods of evaluation or assessment and the types of output for each to ensure they meet the needs of the requestor.This individual will develop training on data: What are the types data are used for portfolio analysis (internal NIH data, patent information, publications, bibliometrics, etc.), what data is available, what is high quality data, and what tools can be used to obtain it.This individual will develop training on technologies (NHLBI, NIH, etc.): Available tools, what questions the various tools can answer, what those answers look like and general knowledge of how to use and when to use. Specific ad hoc tool specific training can be created, or we can share where existing training can be found (i.e., from the Office of Portfolio Analysis in the OD).If suggested by OM, this individual will support the creation of a Learning Library for training: Develop training and resources for portfolio analysis , program evaluations and assessment methods for NIH/NHLBI (e.g., Standard Operating Procedures (SOPs) for analysis, recorded training videos, etc.).This individual will create a comprehensive list of tool specific training available to NIH staff (e.g., OPA, etc.).ResponsibilitiesRequired Skills and Experience:Ph.D. in Evaluation and Applied Research Methods , Computer Science, Data Science, Information Technology, Statistics, or a related discipline.7-10 years of related experience.Strong knowledge of data science, with experience in data processing, data analytics, and visualization of data.Experience developing trainings and learning resources related to analysis, evaluation, and basic data science concepts.Strong knowledge of Machine Learning, Natural Learning Processing, Simple machine learning models like random forest, regression models, etcAbility to build and manage internal and external relationships at all levels within an organization while possessing diplomacy to work effectively with diverse individuals across functional disciplines.Strong analytical skills with ability to define, collect, and analyze data, establish facts, draw valid conclusions, and make logical decisions.Strong organization and prioritization skills.Ability to work in a dynamic, results-driven environment.Ability to think strategically to effectively assess clients’ situation and assemble service solutions to meet clients’ needs.NIH experience.