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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.

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Jobs of Interest to APS

  • Teaneck, New Jersey, The Department of Marketing, Information Systems and Decision Sciences at the Silberman College of Business at Fairleigh Dickinson University is accepting applications for a tenure-track Assistant Professor position in Supply Chain Management based in New Jersey and starting in Fall 2021, contingent on funding. Fairleigh Dickinson founded in 1942, is a private, multi-campus, multi-national, coeducational university with an enrollment of more than 12,000 undergraduate and graduate students from throughout the United States and the world. The Metropolitan Campus (Teaneck, NJ) is located 10 miles from the heart of Manhattan, and the Florham Campus (Madison, NJ) is located on a commuter train line about 35 miles from New York City, near historic Morristown, New Jersey. The University also has overseas campuses in Wroxton, England and Vancouver, Canada, and maintains strong relationships with global partners such as IESEG in Paris, Agder University in Norway, and Zeppelin University in Germany. The multi-disciplinary department provides students with well-rounded, state-of-the-art education in the modern principles of marketing, global logistics/supply chain management, information systems, and decision sciences. We prepare our students for rewarding careers as practitioners and academics, with the help of innovative curricula, dynamic programs, a global mindset, and a professional research ethic. The department consists of 14 tenured-track and 3 non-tenure-track faculty, and a team of 30 practice professionals from the greater New York City region serving as adjunct faculty. Silberman, with over 1400 students at its New Jersey campuses and over 100 students on its Vancouver campus, offers AACSB-accredited undergraduate and graduate programs, and partners with the New Jersey, New York City, and Vancouver business communities to deliver globally-oriented business education programs. Silberman offers seven degree programs: Bachelor of Science (BS); Master of Business Administration (MBA); Master of Business Administration – Management for Executives (EMBA); Master of Science – Accounting (MS-Acct); Master of Science – Taxation (MS-Tax); Master of Science – Supply Chain Management (MS-SCM), and Master of Science – Digital Marketing (MS-DM). Fairleigh Dickinson University is committed to fostering an environment in which faculty, staff, and students from a variety of backgrounds, cultures, and personal experiences are welcomed and can thrive. Silberman College puts high priority on diversity/inclusiveness, experiential learning, and impactful community engagement. Those candidates experienced in, or who would enjoy, working with a diverse range of faculty, staff, and students, and those who can contribute to a culture of inclusivity, are encouraged to highlight their experiences in these areas throughout their application. Essential Duties The successful candidate will demonstrate a commitment to effective teaching, research and the welfare of students by preparing them for success in a multicultural business environment. Duties will be comprised of a balance of teaching, research and service, including the following: Teaching supply chain management as well as related courses at the bachelor's and master's levels on the New Jersey campuses and off-site locations (in face-to-face, online, and/or blended/hybrid modalities). Pursuing and collaborating on a productive research agenda in supply chain management, including publishing in top-tier journals. Mentoring undergraduate and masters students to assist with professional development and career goals. Participating in departmental, college and university service, and service to the discipline. and service to the discipline. Minimum Qualifications Candidates should have a Ph.D. in either Logistics, Supply Chain Management, Transportation, Operations Management, Business Analytics (especially, Supply Chain Analytics), Industrial Engineering, Management Science, or closely related field. Candidates from other disciplines, such as healthcare, with a focus on Supply Chain Management will also be considered. ABD candidates will be considered with a planned completion date by start date. Status as academically qualified, under AACSB standards, to teach at both the undergraduate and graduate levels. Experience with data analytics applications, such as SAS, R, and Python, in various fields of supply chain management, such as forecasting and inventory management, sales and operations planning, transportation, logistics and fulfillment, purchasing and supply management, supply chain risk management. Preferred Qualifications Established academic record in supply chain management teaching and research. Evidence of collaborative research and publications with supply chain management scholars. Record of professional involvement with major professional organizations in the discipline of supply chain management or related rubrics. Ability to work collaboratively with external organizations and stakeholders. Ability to foster partnerships with industry professionals and corporations. Application Review of applications will begin immediately and will continue until the position is filled. For additional information and to apply, please consult FDU's career site (jobs.fdu.edu). Applications will only be accepted online. We intend to conduct interviews remotely and, if conditions allow for a safe visit, to potentially invite successful finalists for campus visits. Complete portfolio must include: A letter of application, A current curriculum vitae, including names and contacts of at least three references, Evidence of teaching effectiveness, Copies of representative scholarly works, or evidence of work in progress, A statement of teaching philosophy, A statement describing experience(s), training, or engagement with issues of diversity, inclusion, and equity, including efforts to work with and support students in an inclusive manner and incorporating topics related to diversity into your courses, and A statement of scholarly achievements and goals. Salary and benefits are competitive with AACSB accredited institutions. Employment is contingent upon a satisfactory background check. Finalists will be required to sign a waiver authorizing the background check and produce a valid Social Security Card. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, national origin, age, disability, or protected veteran status. Fairleigh Dickinson University takes affirmative action in support of its policy to employ and advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities.
  • Chattanooga, Tennessee, About the Position The Data Scientist I will be involved in advanced supply chain analytics covering both deterministic and stochastic modeling, optimization, and analysis.  The position will take business questions, develop model frameworks, identify data sources, extract data, perform quantitative analysis through the model and then develop and communicate insights and/or solution recommendations.  The position should be able to incorporate Artificial Intelligence and Machine Learning to develop Predictive and Prescriptive Analytic models for enhanced decision support. Functions Work with key distribution, transportation, and material handling business managers to identify improvement opportunities through use of advanced data analytics, and develop decision support models for enhanced decision making Provide full-stack data scientist service: the position takes business questions, develops model frameworks, identifies data sources, extracts data, performs quantitative analysis through the model and then develops and communicates insights and/or solution recommendations Incorporate Artificial Intelligence and Machine Learning to develop Predictive and Prescriptive Analytics models for enhanced decision support Support and enhance existing analytics, optimization, and simulation modeling capabilities Routinely perform analysis and make presentations to key business stakeholders, including customers. This position supports the Kenco Operating System (KOS) model of cultural transformation through the integration of operational excellence principles across the enterprise Qualifications Master’s degree in Engineering, Operations Research, Statistics, Computer Science, or related field required. PhD preferred. Minimum of 2 years of experience in Data Science in a business environment required Strong Python skills and experience with using Python to develop Machine Learning and Artificial Intelligence models Ability to write clean and concise code, especially in R or Python Passion to learn new techniques in the space of Machine Learning and Artificial Intelligence Experience using SQL Server, Amazon S3, and Sage Maker Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts and experience with applications Keen eye for detail and thoughtful investigation of data before relying upon it Excellent quantitative modeling, statistical analysis, and problem-solving skills Advanced user of statistical and computer science methods and tools Demonstrated record of dealing with ambiguity and delivering results in a dynamic business environment Preferred: Experience with deploying models on AWS Preferred: Experience in using dashboarding/visualization tools like Qlik or Tableau Competencies Business Acumen - Knowledgeable in current and possible future policies, practices, trends, technology, and information affecting his/her business and organization. Communicate for Impact - Proactively communicate with all stakeholders throughout the life cycle of programs and projects. Influencing Others - Can quickly find common ground and can solve problems for the good of the organization with a minimal amount of noise. Authentically gains trust and support of peers. Managing Transitions/ Change Management - Effectively plans, manages and communicates changes in processes with appropriate stakeholders. Strategic Agility - Enable Kenco to remain competitive by adjusting and adapting to innovative ideas necessary to support Kenco’s long-term organizational strategy. Travel Requirements This position is expected to travel approximately 25% or less.
  • Baltimore, Maryland,   General Summary The Healthcare Data Scientist position will join our Advanced Analytics 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 3+ years of experience with Machine Learning, Predictive Modeling, Statistical Analysis, Mathematical Optimization, Algorithm Development 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 UMMS Vice President for Enterprise Data and Analytics (ED&A).   Principal Responsibilities and Tasks Develops and manages 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. Conducts advanced and strategic analysis based in evidence and statistical methodologies. Deploys solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems. Supports and drives analytic efforts designed around organization’s strategic priorities and clinical/business problems. Works in a team to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements. Builds and extends our analytics portfolio supported by robust documentation Works with autonomy to find solutions to complex problems using open source tools and in-house development. Stays abreast of state-of-the-art literature in the fields of operations research, statistical modeling, statistical process control and mathematical optimization. Creates and communicates project plans and other required project documentation and provides updates to leadership as necessary. Develops and maintains relationships with business, IT and clinical leaders and stakeholders across the enterprise to facilitate collaboration and effective communication. Works with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings. Performs analysis to evaluate primary and secondary objectives from such pilots. Assists leadership with strategies for scaling successful projects across the organization and enhances the analytics applications based on feedback from end-users and clinical/business consumers. Assists leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization. Knowledge, Skills and Abilities Ability to develop (from scratch) machine learning and/or deep learning approaches to solving clinical and business (including operations, supply chain, human resources, finance) problems. Knowledge of databases, data structures, data processing and data mining. Ability to perform basic and advanced statistical analysis. Ability to perform independent/unsupervised exploratory data analysis. Ability to develop complex process models using discrete-event-simulation. Ability to program independently in Python (intermediate skills); ability to participate in software platform and web application development. Proven communications skills – Effective at working independently and in collaboration with other staff members. Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics. Proven analytical skills – Able to compare, contrast, and validate work with keen attention to detail. Skilled in working with “real world” data including scrubbing, transformation, and imputation. Proven problem solving skills – Able to plan work, set clear direction, and coordinate own tasks in a fast-paced multidisciplinary environment. Expert at triaging issues, identifying data anomalies, and debugging software. Design and prototype new application functionality for our products. Change oriented – actively generates process improvements; supports and drives change, and confronts difficult circumstances in creative ways. Effective communicator and change agent. Ability to prioritize the tasks of the project timeline to achieve the desired results Strong analytic and problem solving skills. Ability to cooperatively and effectively work with people from various organization levels. Education and Experience Master’s or higher degree (may be substituted by relevant work experience) in applied mathematics, engineering, operations research, physics, computer science, statistics or a related field. PhD degree preferred. Background in computer science, operations research, statistics or a physical engineering discipline. 3+ years of Machine Learning/Predictive Analytics and Mathematical Optimization experience (to include time in graduate program for applicants with PhD degrees). Prior experience with Python and R is a must (experience with tools such as WEKA, RapidMiner, or other open source tools are strongly preferred). Ability to develop and apply computational algorithms and statistical methods to healthcare data (including, but not limited to data from electronic medical record, financial management, human resource, quality and supply chain) Ability to develop and deploy healthcare-relevant predictive and prescriptive models. Ability to perform standard and advanced statistical analysis. Ability to formulate and solve mathematical (deterministic and stochastic) optimization problems and simulation; prior experience in Arena, FlexSim or similar environments. Experience with discrete-event-simulation strongly preferred. Robust experience with SQL Intermediate development skills in Python. Ability to combine analytic methods and advanced data visualizations. Experience with Big Data technologies, including Hadoop. Expert ability to break down and clearly define problems. Experience with text mining and Natural Language Processing (NLP) desirable. Incentive Plan Offered. Competitive medical, dental and retirement benefits.

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