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 are building the nation's first stand-alone could-based open RAN 5G network.
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.
DISH is looking for a Data Science Manager
work closely with teams like product, engineering, marketing, operations, and help solve some of their problems from a data perspective.Primary responsibilities
fall into the following categories:
If you meet most of the following requirements
- Plan: Deeply understand the business requirements and priorities and work with other stakeholders to identify high-impact and feasible roadmap areas for the team from time to time. The fact that the business teams may not understand how data science could help their work makes this very challenging.
- Execute: Own the deliverables of the team and be in charge of the estimation and planning done by the team making sure that the dependencies are tracked correctly, and results are produced in an efficient and timely manner.
- Guide:Act as a technical guide to the team helping them in translating the business problems to the most appropriate mix of specific machine learning or data analysis tasks. Also be a mentor to the team members.
- Facilitate: Be an evangelist of best practices, the right tools and effective collaboration. Proactively create a great working environment where each individual brings out the best they can offer.
- Communicate:Be the point of contact for the team's work for the business teams and senior management. Create and deliver effective presentations at various stages of the projects to different audiences involved.
, you are likely to be a great fit for the position:
Additional Preferred qualifications
- You have a strong academic background in statistics and machine learning. The typical candidate has a Bachelor's or Master's degree in Math, Statistics, Computer Science, Physics or such quantitative fields or has done a program from a business school in marketing, analytics etc. with a focus on quantitative approaches.
- Overall 4+ years with all of your experience were related to data and data analysis. You have worked on a variety of complex data analysis and modeling problems, gathering a great deal of practical wisdom on how to apply these techniques to real world scenarios.
- You have a wide range of statistical and machine-learning tools under your belt. These include linear models for regression and classification, ensemble models, factor analysis & PCA, discriminant analysis, support vector machine, decision tree ensembles & bootstrap, neural networks, mixture models & clustering algorithms, and so on. You are proficient in at least one programming language commonly used for data analysis (like R/Python), and you are cozy with SQL.
- Previously worked on business analytics problems like customer churn, lifetime value estimation, targeted marketing, personalized offers, etc. And experienced in designing & analyzing controlled experiments for targeted interventions in the field
- Masters or Doctorate in relevant domain.
- Possess strong data visualization skills using programmatic tools (e.g. ggplot2, shiny, d3.js) and other visualization frameworks like victory, highcharts etc. This will be a strong plus.
- Knowledgeable on different database and data warehousing systems like MySQL, Amazon Redshift, BigQuery, Teradata
- Experienced in working with large data sets, with big data processing tools like Spark.
- Have data engineering skills to do preprocessing, cleaning and transformations.
Compensation: $100,625.00/Year - $186,875.00/Year
From versatile health perks to new career opportunities, check out our benefits on our careers website.
Candidates need to successfully complete a pre-employment screen, which may include a drug test.