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The Applied Probability Society is a subdivision of the Institute for Operations Research and the Management Sciences (INFORMS). The Society is concerned with the application of probability theory to systems that involve random phenomena, for example, manufacturing, communication network, computer network, service, and financial systems. The Society promotes the development and use of methods for the improvement of evaluation, control, and design of these systems. Such methods include (stochastic) dynamic programming, queueing theory, Markov decision process, discrete event dynamic systems, point processes, large deviations, reliability, and so on. Our members include practitioners, educators, and researchers with backgrounds in business, engineering, statistics, mathematics, economics, computer science, and other applied sciences.

The Applied Probability Society also publishes Stochastic Systems. This open-access journal seeks to publish high-quality papers that substantively contribute to the modeling, analysis, and control of stochastic systems. The contribution may lie in the formulation of new mathematical models, in the development of new mathematical methods, or in the innovative application of existing methods. A partial list of applications domains that are germane to this journal include: service operations; logistics, transportation, and communications networks (including the Internet); computer systems; finance and risk management; manufacturing operations and supply chains; and revenue management.

To keep up-to-date with all the latest developments in the Applied Probability Society community, INFORMS members should make sure to subscribe for real-time or digest correspondence through INFORMS Connect. For INFORMS members outside of the Society or for community members outside of INFORMS who would like to receive updates as well, register here to receive select Applied Probability Society communication directly.

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Jobs of Interest to APS

  • Arlington, Virginia, PRIMARY PURPOSE CNA is hiring for an  Operations Research Analyst  to join their  Resources and Force Readiness Division  (RFR). Staff at this level will be leading smaller/less complex activities  or will be serving as an important contributing team member on projects.  The RFR division focuses on a full range of resource issues. Six programs within RFR address problems in manpower, personnel, training and education; energy, infrastructure and the environment; cost, acquisition processes, material and supply readiness and logistics; and health analytics and medical readiness. CNA fosters an inclusive culture that values diverse backgrounds and perspectives. Our flexible and engaging work environment encourages iterative and creative collaboration at every stage of the problem solving process. Our employees are committed to helping clients develop effective solutions to better manage their programs through scientific, data-driven approaches. We are looking for creative and innovative individuals to help carry out our mission.  JOB DESCRIPTION AND / OR DUTIES With minimal or no guidance, meets CNA’s quality standards when working on well-structured pieces of a project. Demonstrates ability to develop sound analytic frameworks and associated analytic methodologies/ techniques for addressing both structured and unstructured problems.  With direction and supervision, clearly defines, structures, and executes a piece of a complex study to meet quality standards.  Demonstrates analytic creativity and curiosity. Develops and maintains broad, general institutional knowledge of primary clients/sponsors; their culture, organization, and issues. Contributes productively and harmoniously to the work of others; treats everyone respectfully, professionally and fairly.  Keeps others informed.  Proactively identifies and seeks out others working on similar topics.  Works to identify opportunities for collaborations within team, division, and operating unit. Supports business development efforts and/or marketing activities by maintaining strong client relationships through high quality work, increasing the visibility of our work, and other related activities such as proposal preparation. Interacts with sponsors/clients under the supervision of an experienced colleague, and with study POCs independently. Makes significant contributions to research publications and analytic products for individual projects. Demonstrates ability to communicate results of work in a clear and concise fashion.  Effectively communicates one-on-one and in groups.  Can document work efficiently and accurately. Can effectively present work to colleagues, sponsors, and small audiences that are familiar with content. Works with minimal or no guidance on focused, well-structured pieces of projects.  Works under closer supervision on more complex, less-structured tasks.  Can serve as task lead for pieces of projects by managing own activities.  May lead small projects under the supervision of an RPD. Exhibits a positive attitude in interactions with colleagues and clients/sponsors.  Provides clear guidance to colleagues on tasks.  Takes responsibility for own actions and outcomes. Other duties as assigned. JOB REQUIREMENTS Education: Minimum Master’s degree in  operations research, systems engineering, industrial engineering, or in a field closely related to decision-making optimization , PhD preferred. Experience: Typical minimum requirements Ph.D. & 0+ years or Master’s & 2+ years of experience in: Developing and parameterizing mathematical programs, such as linear, integer, quadratic and/or stochastic programs. Using optimization to inform analysis of tradeoffs and business cases to support resourcing decisions. Developing and coding simulation models using interpreted programming languages (R and Python) and commercial off-the-shelf software (Arena and ExtendSim). Interpreting results of simulation models to inform decision making and evaluate alternative courses of action. Experience in applying optimization and simulation techniques in the fields of personnel management and/or human resource management is highly desired. Skills: Ability to make significant contributions to projects/analyses Strong analytic curiosity/ creativity Ability to operate independently in the execution of assignments Ability to work in a multi-disciplinary environment Strong critical thinking skills Knowledge of research techniques Strong planning and organizational skills Excellent interpersonal, oral and written communication skills Ability to interact positively and somewhat independently with clients. 4. Hybrid Work Eligibility: This position is eligible for hybrid work arrangements at the discretion of the Supervisor. Employees may be required to work at CNA headquarters or other work locations resulting in changes to the scheduled hybrid work arrangements. 5. Other: Ability to obtain and maintain an Active Secret Security Clearance.  Required Documents Please include the following documents with your application: Resume or CV Cover letter  - Please upload a cover letter as part of your application that introduces yourself, summarizes your relevant skills and experiences, and describes why you would be a valuable asset to CNA’s RFR Division. Transcripts  - Please upload your undergraduate and graduate transcripts (unofficial copies are acceptable). Writing Sample  - Please upload a research paper or journal article that demonstrates your writing and research skills (draft copies are acceptable) Optional Documents Letters of Recommendations  – In a later stage of the hiring process, we will require 1-2 letters of recommendation. To have them considered as part of your application now, please upload them with your resume or CV. ***Voluntary (but highly desired) document*** Please include a personal statement as part of your application. A personal statement is a chance for us to get to know you. The statement is your opportunity to share your goals, interests, influences and show us that you will be a valuable asset to our organization. Please click here for personal statement guidelines –  Click here Personal statements will not be used as an elimination criteria for this position. They will only be used to enhance a candidate’s application
  • North Bethesda, Maryland, Company Description The University of Maryland Institute for Health Computing (UM-IHC) is a strategic collaborative between the University of Maryland, Baltimore (UMB) and the University of Maryland, College Park (UMCP), and the University of Maryland Medical System. Based in North Bethesda, MD, the institute focuses on artificial intelligence and advanced computing to further develop the field of precision medicine to improve well-being, quality of life, diminish disease, and enhance health outcomes for all citizens of Maryland and beyond. General Summary The Healthcare Data Scientist - Machine Learning/AI, Statistics, Operations Research position will join our Advanced Data Science group at the University of Maryland Medical System (UMMS) in support of its strategic priority to become a data-driven and outcomes-oriented organization. The successful candidate will have experience with Machine Learning/AI, Statistics and Operations Research and a passion for working with healthcare data. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. This position will report to the Director for Advanced Data Science & Consulting Services. This position has a hybrid work structure, where working from the office at regular intervals will facilitate building collaborations among the interdisciplinary teams at the IHC. Principal Responsibilities and Tasks Support analytic efforts designed around the organization’s strategic priorities and clinical/business problems. Develop predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities. Deploy solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems. Work with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings . Perform statistical analysis to evaluate primary and secondary objectives from such pilots. Support development of strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization. Build and extend our analytics portfolio supported by robust documentation. Work in a team to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements. Assist leadership with strategies for scaling successful projects across the organization, and enhance the analytics applications based on feedback from end-users and clinical/business consumers. Assist leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization. Work with autonomy to find solutions to complex problems using open source tools and in-house development. Stay abreast of state-of-the-art literature in the fields of machine learning/AI, operations research, statistical modeling, statistical process control and mathematical optimization. Education and Experience PhD degree in applied mathematics, data science, physics, computer science, engineering, statistics, economics or a related field required; comparable work experience may be substituted for the PhD degree. Preferred 3+ years of industry experience in the following: Machine Learning/AI, Statistics or Operations Research. Programming with SQL, Python and R. Practical experience with machine learning/AI problems, or formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation, or performing advanced statistical analysis. Developing and applying computational algorithms and statistical methods to healthcare data (including, but not limited to data from electronic medical record, financial management, human resources, quality and supply chain). Developing and deploying healthcare-relevant predictive and prescriptive models. Combining analytic methods and advanced data visualizations. Text mining and Natural Language Processing (NLP) is preferred. Knowledge, Skills and Abilities Develop (from scratch) machine learning and/or deep learning approaches and algorithms to solve clinical and business (including operations, supply chain, human resources, finance) problems. Formulate and solve complex mathematical optimization problems using exact and heuristic approaches. Perform independent/unsupervised exploratory data analysis and advanced statistical analysis (e.g., regression analysis, cluster analysis, factor analysis, ANOVA). Design and prototype new application functionality for our products. Work with “real world” data including scrubbing, transformation, and imputation. Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics to stakeholders at various organization levels. Knowledge of databases, data structures, data processing and data mining from large enterprise transaction systems (e.g., Epic, Infor/Lawson, McKesson HPM, Payer Claims or similar applications in healthcare or other industries). Effective at working independently and in collaboration with other staff members for software platform and web application development. Cooperatively and effectively work with people from various organization levels. Manage projects to meet organizational goals. Plan work, set clear direction, and coordinate own tasks in a fast-paced multidisciplinary environment, including triaging issues, identifying data anomalies, and debugging software. Able to compare, contrast, and validate work with keen attention to detail. Actively generate process improvements; support and drive change, and confront difficult circumstances in creative ways.

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