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Lake Buena Vista, Florida, Job Description We seek candidates for roles at multiple levels within the Decision Science team. The specific job level for an individual candidate will be determined based on their education, prior experience, and demonstrated technical and leadership proficiencies. The Decision Science team focuses on creating innovative mathematical models to inform business decision making through data. The team is interested in all fields related to data science, with emphasis on statistics, operations research, econometrics, and machine learning. The Decision Science team resides within the Disney Decision Science + Integration (DDSI) organization. DDSI provides internal consulting services for clients across The Walt Disney Company, including Disney Parks, Experiences and Products (covering Parks & Resorts, Signature Experiences, and Consumer Products, Games and Publishing) and Disney Media & Entertainment Distribution (covering content from Studios, General Entertainment and Sports). The DDSI team sits at the intersection of business strategy, advanced analytics, and technology integration to help our partners explore opportunities for analytics, shape business decisions, and drive value. Our work includes conceptualizing new solutions, solution design and development, implementation and integration with business processes, and ongoing business support.   Responsibilities Achieve business goals and objectives—Research and develop decision science models and act as a consultant to all business units within The Walt Disney Company Pursue innovation—Conduct research on analytical techniques and translate that research into usable and sustainable solutions for users Put your skills to the test—Perform data collection and data mining, and build state-of-the-art decision science algorithms, tools, and systems Drive value—Model and analyze revenue management and pricing related issues using various mathematical, statistical, and simulation techniques Tell the story—Present science results to business partners and clients Support a global and enterprise-wide mission—Identify and apply best practices in the field of advanced analytics for multiple businesses such as theme parks and resorts (e.g. Walt Disney World), Disney Cruise Line, media (e.g. ABC, ESPN), movies (e.g. Walt Disney Animation Studios), live shows (e.g. Disney on Broadway), and retail (e.g. shopDisney) Basic Qualifications Must exhibit competence in at least one of the following four analytical fields, inclusive of topics as noted: Statistics (two or more topics): Bayesian statistics Generalized linear models Mixture models Nonparametric regression Structural equation models Time series (state space models, ARIMA, etc.) Optimization (at least one topic): Decision analysis or multiple criteria decision making Mixed-integer optimization Nonlinear optimization Stochastic optimization Discrete-event simulation and stochastic models Econometrics (two or more topics): Generalized method of moments Instrumental variables Limited dependent variables Panel data Simultaneous equations models Machine learning (two or more topics): Boosting CART Clustering Graphical models Neural networks Random forests Reinforcement learning Support vector machines Must exhibit competence in at least one computing topic: General computing (Python, Java, C, C++, etc.) Statistical computing (R, SAS, etc.) Scientific computing (Julia, MATLAB, etc.) Roles beyond the entry level require the ability to work with little guidance on science methodologies and modeling approaches, based on sound business acumen, and to provide peer leadership to junior colleagues Higher roles require the ability to work concurrently across lines of business or functional areas, to direct the design and development of advanced analytical models, or to provide project leadership to ensure successful implementation of solutions across all project phases Preferred Qualifications Proven knowledge of revenue management context, including demand forecasting, resource allocation, and pricing Required Education Master’s or Ph.D. degree in Statistics, Operations Research, Industrial Engineering, Mathematics, Machine Learning, Econometrics, or related field

Washington, D.C., Senior Consultant , Guidehouse Inc., Washington, DC. Support the management of workstreams on client engagements from inception to completion. Develop work products that require understanding of clients’ organizations and business and regulatory environment. Research and review documentation to identify best practices to improve financial management business processes. Apply expertise in accounting standards, Agile methodologies, data analytics, forecasting/modelling, and change management. Assist management with identifying public sector opportunities to support Federal clients with implementation and execution of laws, regulations, and guidance that govern their business processes.   40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. MINIMUM REQUIREMENTS : Bachelor’s degree or foreign equivalent degree in Business, Accounting or a related field, and 3 years of post-bachelor, progressive, related work experience. Must have 1 year of experience with/in: Developing financial forecasting and pricing models; Developing and implementing Microsoft office tools (such as Excel and/or Visio) for data collection and analysis; Software applications Tableau and Salesforce; Developing proposals that respond to requirements listed in statements of work; and Managing project budgets and schedule of activities to ensure submission of client deliverables. 20% travel required. Telecommuting permitted. Please apply by mail to: Ronald McKnight, Guidehouse Inc, 2941 Fairview Park Drive, Suite 501, Falls Church, VA 22042. Please reference Job-ID: DC0009

Chicago, Illinois, Position Description The University of Chicago’s Physical Sciences Division invites applications for the position of lecturer for the 2021-22 academic year to teach at least two core or elective courses for the Master of Science in Analytics program. See below for a list of courses. Administrative duties may also be assigned. Lecturers will be appointed to an initial one year term (calendar year), with the possibility of renewal. For more detailed course descriptions, visit https://professional.uchicago.edu/find-your-fit/masters/master-science-analytics/curriculum.   This position is part-time and not benefits eligible. Applicants must currently be authorized to work permanently in the United States. These courses are offered at our downtown facilities, including NBC Tower and Gleacher Center.  Core Courses  Time Series Analysis and Forecasting | MSCA 31006  Statistical Analysis | MSCA 31007  Data Mining Principles | MSCA 31008  Machine Learning and Predictive Analytics | MSCA 31009  Linear and Nonlinear Models for Business Application | MSCA 31010  Data Engineering Platforms | MSCA 31012  Leadership Skills: Teams, Strategies, and Communications | MSCA 31003  Data Science for Consulting | MSCA 31015  Elective Courses  Big Data Platforms | MSCA 31013  Financial Analytics | MSCA 32001  Marketing Analytics | MSCA 32003  Credit and Insurance Risk Analytics | MSCA 32004  Real Time Analytics | MSCA 32005  Data Visualization Techniques | MSCA 32007  Health Analytics | MSCA 32009  Optimization and Simulation Methods for Analytics | MSCA 32013  Bayesian Methods | MSCA 32014  Digital Marketing Analytics in Theory and Practice | MSCA 32015  Advanced Machine Learning and Artificial Intelligence | MSCA 32017  Natural Language Processing and Cognitive | MSCA 32018  Real Time Intelligent Systems | MSCA 32019  Reinforcement Learning | MSCA 32020  Machine Learning Operations | MSCA 32021 Qualifications Minimum qualifications: A master’s degree in Data Science, Applied Math, Statistics, Computer Science, Mathematics, or other closely related field, and minimum of five years of professional experience in Computer Science, Analytics, or Data Science is required.  Preferred qualifications: a PhD in Data Science, Applied Math, Statistics, Computer Science, Mathematics, or other closely related field. One to three years of teaching experience either within a university (such as Adjunct, Lecturer or Instructional Professor) or corporate training environment for professional education is preferred. 7+ years of professional experience preferred.  Application Instructions The following materials are required:  CV;  Cover letter that lists the courses you are most qualified to teach; A list of two references; Sample course syllabus; Teaching statement; Optional materials: teaching evaluations from past teaching at the university level. Applications must be submitted online through the University of Chicago’s Academic Jobs website:  apply.interfolio.com/97358 .  Equal Employment Opportunity Statement We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages diverse perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange. The University’s Statements on Diversity are at  https://provost.uchicago.edu/statements-diversity . The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's  Notice of Nondiscrimination . Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-1032 or email  equalopportunity@uchicago.edu  with their request.

San Francisco, California, The Opportunity:   Flexport is looking for a creative, technically-minded Senior Applied Research Scientist (ARS) who is motivated to solve some of the world’s most challenging problems in global trade.   Data is at the heart of our business, and as a Senior ARS, you will work to evaluate and provide insights into our physical and digital products. In collaboration with multidisciplinary product, engineering, and business/operations teams, you will apply advanced Machine Learning (ML) and Operations Research (OR) methods to deliver data-driven insights and automated decision-making in Flexport’s freight forwarding products.  Our business, product, and engineering teams collaborate closely with our Applied Research Scientists to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. We are passionate about providing effortlessly accessible intelligence and actionable insights to our end users. Our ideal candidate is: self-motivated, highly analytical, technically excellent at writing code, and passionate about delivering cutting-edge solutions.   You Will: Work collaboratively with product, engineering, and business to: find opportunities to improve and enhance our technology products,  understand Flexport’s business and operations processes to identify impact opportunities, and translate ambiguous business requirements into the right technical/quantitative solution. Perform requirements gathering and data gathering & analysis.   Research prior work to inform and develop models and algorithms and quantify appropriate metrics & targets. Perform R&D of new models/algorithms and refactor ML/OR solutions to support scalable production deployment.  Deliver compelling data-driven solutions to support automated decision-making at scale. Work with large and complex data sets. Solve difficult data analysis problems by applying advanced analytical methods as needed.  Develop prototype data analyses and data assets iteratively as needed to generate actionable insights.  Communicate findings to technical collaborators and business stakeholders.  Drive and hands-on contribute to model/algorithmic development.   You Should Have: Minimum Qualifications Ph.D. (or equivalent industry or research experience) in quantitative fields, such as Operations Research, Computer Science, Mathematics, etc.  5+ years of hands-on experience in predictive and quantitative modeling and analysis. Experience and strong expertise in business analytics, forecasting, or supply chain planning, emphasizing quantitative modeling and analysis. Experience and a strong background in algorithm design, engineering, and implementation. Experience and a strong background in optimization methods for solving linear, mixed-integer, and dynamic programs. Understanding of MIP strategies to customize/leverage commercial/open-source solvers.  Software development experience using general-purpose programming languages like Python, Java, or C/++, C# Experience working with large data sets and knowledge of tools for big data analytics (e.g., SQL, Python, Perl, or Ruby). Preferred Qualifications Knowledge of decomposition/iterative methods for solving large-scale optimization problems. Expertise in designing and implementing optimization models and algorithms for large-scale discrete/combinatorial problems (e.g., vehicle routing, inventory planning, scheduling, network design, scheduling, and facility location). Expertise in developing metaheuristics and matheuristics algorithms for extreme-scale combinatorial optimization. Experience taking research prototypes to production. Some experience in business analytics, forecasting, or supply chain planning, emphasizes quantitative modeling and analysis. Some experience in machine learning and statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and experimental design. Proven object-oriented design and implementation skills (Python, Java, and C++). Understanding of scalable computing systems, software architecture, and data structures. Experience leading the development of complex software systems that have been successfully deployed. Knowledge of software engineering best practices for the complete software development life cycle. Strong research track record with contributions to research communities via publications in top conferences and journals and code contributions in open source communities such as COIN-OR, scikit-learn, CLTK, NLTK, etc.   About Flexport   We believe trade can move the human race forward. That’s why it’s our mission to make global trade easy for everyone . Flexport is building the platform for global logistics, empowering buyers, sellers and their logistics partners with the technology and services to grow and innovate. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $10B of merchandise across 112 countries every year.   Worried about not having any logistics experience?   Don’t be! Our mission is to make global trade easy for everyone . That’s why it’s important to bring people from diverse backgrounds and experiences together with our industry veterans to help move the global logistics industry forward. We know this industry is complex. That’s why we invest in education starting day one with Flexport Academy, a one week intensive onboarding program designed specifically to set every new Flexport employee up for success.  At Flexport, our ability to fulfill our mission of making global trade easy for everyone relies on having a diverse, dedicated and engaged workforce. That is why Flexport is committed to creating and nurturing an environment where anyone can be their authentic self. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, national origin, age, physical and mental disability, health status, marital and family status, sexual orientation, gender identity and expression, military and veteran status, and any other characteristic protected by applicable law.

San Francisco, California, The Opportunity   Flexport is looking for a creative, technically-minded Applied Research Scientist (ARS) Intern who is motivated to solve some of the world’s most challenging problems in freight forwarding.     Data is at the heart of our business. As an ARS Intern, you will evaluate and build quantitative solutions for Flexport’s freight forwarding and marketplace products. In collaboration with multidisciplinary teams, you will apply advanced methods to develop operations research/machine learning solutions that deliver data-driven insights and automated decision making. Project assignment will be based on the team's needs and your knowledge and skillsets.    You will own end-to-end delivery of the science solution over 12 weeks, culminating in delivering and presenting a production-ready solution.  The science team has intern projects covering all Flexport initiatives, including pricing, experimentation, strategic/tactical/operations planning (e.g., routing, scheduling, inventory management, and network design), and applied machine learning (e.g., transit time estimation, forecasting, trade & financial services). You Will: Lead and complete at least one science project that will be launched in production. Work with a supportive mentor who has a stake in your success and will help you grow. Perform data gathering and requirements gathering & analysis.   Research prior work to inform and develop rational hypotheses and quantify appropriate metrics & targets.  Develop data analysis/machine learning solutions to support actionable insights and deliver data-driven OR solutions to support automated decision making. Work with large and complex data sets and solve difficult data analysis problems by applying advanced analytical methods as needed.  You Should Have: Minimum Qualifications Be a Ph.D. candidate within one year of graduation in a technical field like Operations Research, Applied Mathematics, Statistics, Computer Science, Engineering, etc. Have strong programming experience in SQL and one or more of the following languages: Python, C/C++, C#, Java.  Experience working with large data sets and knowledge of tools for big data analytics (e.g., SQL, Python, Perl, or Ruby). Practical exposure to algorithm design, engineering, and implementation. Practical exposure to optimization methods for solving linear, mixed-integer, and dynamic programs. Ability to translate business requirements into mathematical models.  Knowledge of MIP strategies to customize/leverage commercial/open-source solvers.  Knowledge of business analytics, forecasting, or supply chain planning, emphasizes on quantitative modeling and analysis.   You will get: An assigned manager and mentor who will be dedicated to your success at Flexport.  Projects and assignments which will help build your knowledge and skills while making a measurable direct impact on the business. Visibility to leaders within the organization and opportunities to present your work/projects. Opportunity to join team-building activities to get you familiarized with your immediate team and other Flexport employees. About Flexport: We believe trade can move the human race forward. That’s why it’s our mission to make global trade easy for everyone . Flexport is building the platform for global logistics, empowering buyers, sellers and their logistics partners with the technology and services to grow and innovate. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $10B of merchandise across 112 countries every year.