Together, we’re reimagining the future.
At DISH Wireless, we reimagine connectivity through new platforms, new business models and new ways of thinking.
Today, we are building America’s first cloud-native 5G network to transform the way we live, work and play with unlimited potential. Our teams operate at the intersection of wireless, data analytics, AI and the cloud to create something state-of-the-art, radically original, and truly unlike what anyone else can.
Navigating an ambiguous future, our mission is clear. We adapt to, and drive, change for all.
Job Duties and Responsibilities
The Data Science Engineer is responsible for building AI/ML solutions to identify insights, predictions and recommendations using the DISH Wireless Commercial data providing value to the DISH business team and build analytics product offerings in the marketplace for Commercial customers. This individual will play an active role in delivery and ensure alignment to the end-state architecture.
Day-to-day job responsibilities:
- Provide technical expertise in Advanced Analytics
- Discover information hidden in vast amounts of data, and help make smarter decisions to deliver a better product and service
- Process, cleanse, and verify the integrity of data used for analysis
- Work with various business units to develop automated data science solutions that add business and customer value
- Translate complex data science concepts to business understandable insights
Skills, Experience and Requirements
- 5+ years of hands-on Data Science development experience with delivering secure, reliable and scalable data science solutions using agile methodologies
- Strong coding experience in SQL and Python or R or Scala
- Experience using popular data science libraries (i.e. scikit-learn, Spark ML, TensorFlow, etc.)
- Experience in Machine Learning, Forecasting and Optimization techniques, find right data and solve problems
- Knowledge and experience with TDD, CI/CD, cloud native and 12 Factor Apps
- Experience working with containerization platforms (Docker, Kubernetes)
- Experience in handling Big Data, streaming data, relational databases and unstructured data
- Degree in Statistics, Mathematics, Computer Science, or Information Technology or equivalent professional experience (Master’s degree is preferred)
- Experience with AWS and Snowflake
- Experience with AutoML tools like DataIKU or H2O.ai
- Experience in building dashboards using BI tools like Tableau and Power BI
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