Data Scientist II
US-CO-Englewood
Attract-careers1
Req #: 92915
Type: Fulltime-Regular
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Responsibilities: Data Scientist II sought by DISH Network in Englewood, CO. The primary focus is developing and deploying Classical Artificial Intelligence/Machine Learning (AI/ML) and Generative AI (GenAI) models tailored for wireless and pay-TV applications. This role requires close collaboration with Data Scientists and Engineers & Stakeholders to design data products that optimize revenue streams and enhance user experiences. Key responsibilities include: * Developing and deploying Classical AI/ML and GenAI models for wireless and pay-TV applications. * Collaborating with cross-functional teams to design data products aimed at optimizing revenue streams and improving user experiences. * Performing data quality checks, conducting Exploratory Data Analysis (EDA), and preparing data for modeling (handling null values, categorical fields, and continuous values). * Data wrangling to ensure format consistency and implementing feature engineering and selection techniques. * Creating interactive data visualizations and developing business consoles. * Fine-tuning AI/ML models for prediction, analysis, and optimization. * Presenting findings and recommendations to executives. * Staying updated with the latest advancements in AI/ML to enhance model performance. * Deep understanding of the current IT infrastructure, DISH data, and tribal knowledge to ensure right customizations and efficient delivery The team's objective is to apply AI/ML and GenAI methods to solve business problems and optimize operations across various brands in wireless and pay-TV services. You will collaborate closely with business teams to define product objectives and integrate AI capabilities seamlessly. Qualifications: Requires: Bachelor's degree (or foreign equivalent) in Computer Science, Electrical Engineering, or closely related field plus 1 year of experience in job offered, or as Data Scientist, or closely related role. Also requires 1 year of experience with/using the following (which may have been gained concurrently): * Python, Go, R, Grafana, ELK, Tableau, AWS Quicksight * CI/CD pipelines, infrastructure automation, and a container-based software environment; ETL, AWS Athena, BigQuery, Spark, Hadoop, Hive, Impala; * EC2, S3, EMR, EKS, Cloudwatch, Redshift.
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