DISH

Operations Research - Business Optimization

US-CO-Littleton
Job ID
2017-41677
Category
Customer Service Center (CSC)

Summary

DISH is a Fortune 200 company with more than $15 billion in annual revenue that continues to redefine the communications industry. Our legacy is innovation and a willingness to challenge the status quo, including reinventing ourselves. We disrupted the pay-TV industry in the mid-90s with the launch of the DISH satellite TV service, taking on some of the largest U.S. corporations in the process, and grew to be the fourth-largest pay-TV provider. We are doing it again with the first live, internet-delivered TV service – Sling TV – that bucks traditional pay-TV norms and gives consumers a truly new way to access and watch television.

 

Now we have our sights set on upending the wireless industry and unseating the entrenched incumbent carriers.

 

We are driven by curiosity, pride, adventure, and a desire to win – it’s in our DNA. We’re looking for people with boundless energy, intelligence, and an overwhelming need to achieve to join our team as we embark on the next chapter of our story.

 

Opportunity is here. We are DISH.

Job Duties and Responsibilities

DISH currently has an opportunity for a strongly motivated Operations Research / Business Optimization Specialist within a Modeling and Analytics team. This team serves Customer Support Center (CSC) workforce operations, among other teams.  We have multiple openings in the Denver area for professionals who are inquisitive self-starters.

 

Primary responsibilities fall into the following categories:

 

  • Identify, define, design, and adapt rigorous quantitative approaches into delivered operational value through optimization and analysis
  • Specifically, assist in the development of analytical infrastructure, processes, and capabilities as an internal consultant which supports and informs decision making in a variety of implementation scenarios
  • Work alongside data science, data engineering, and IT teams to operationalize models which hold value
  • In addition to utilizing standard descriptive and predictive methodologies, the scope of the job includes the design and development of solutions and applications for workforce optimization, including modeling and simulation

Skills - Experience and Requirements

A successful candidate will have experience with:

  • Modern optimization modeling languages and solvers, including taking simulation approaches to problems
  • Operationalizing and deploying solutions which deliver value derived from optimization
  • Applicants should have degrees in Operations Research, Applied Mathematics, Computer Science, Statistics, or other related disciplines (e.g., Industrial Engineering, Service Engineering, Behavioral Operations Research, Actuarial Sciences, Management Science)
    • Individuals with multidisciplinary skill sets (e.g., data science, computational mathematics, engineering, programming, machine learning, data modeling, database design, workforce domain knowledge, reporting) are strongly encouraged to apply
    • Graduate degree(s) and additional years of experience are highly preferred


 

Additional Qualifications
(Experience working in any of the following domains or with any of the following technologies is each a plus.)

  • Broad experience in business requirements analysis, analytical application design
  • Multiple programming and scripting languages (e.g., Java, Python, R, Scala)
  • Large database SQL platforms as well as wide-column or NoSQL stores, and related environments, frameworks, and engines (e.g., Teradata, Redshift/ParAccel, Hadoop, Hive, HBase) and newer data platforms
  • Sector experience or familiarity with classes of problems which include workforce optimization, rostering, or similar (or, more generalized practical experience with doubly stochastic processes)
  • Working in, or with, teams on related technical areas such as cluster computing frameworks, learning engines and libraries, and graph databases (Spark, TensorFlow, Mahout, deeplearning4j, neo4j etc.), anomaly detection, data mining, advanced analytics, streaming analytics, anomaly detection, exploratory data analysis, ETL, risk analysis, graph/network analysis, data visualization, text mining, and their enabling technologies
  • Simplifying apparent multiple-objective systems, confronting practical multiply-constrained systems, specifying integration and preparation of larger data sets (including previously untapped ‘deep’ data sources)

If you meet these requirements and have interest in these domains, we would like to hear from you.

 

Nature and Scope

This position has no direct reports, and requires overnight travel less than 10% of the time.

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