The Data and AI Products team at DISH is looking to innovate across satellite and wireless by applying machine learning, advanced analytics, and generative AI to real-world challenges. The Data Science & AI Manager will lead a team to develop, deploy, and improve predictive and generative AI solutions, impacting strategy and product experiences.
Requirements
- Hands-on experience with machine learning models (classification, regression, clustering, time series, etc.) and LLM/GenAI applications
- Skilled in Python and SQL; familiarity with cloud environments (preferably AWS)
- Experience with platforms such as Dataiku, Databricks, or SageMaker for scalable ML/AI workflows
- Familiarity with customer lifecycle analytics, personalization, or NLP on support interactions
- Exposure to MLOps and model governance best practices
Responsibilities
- Provide technical guidance on model design, experimentation, and code quality while fostering a culture of rigor, curiosity, and collaboration
- Lead the development and productionization of predictive (e.g., churn, CLV, segmentation) and generative AI solutions (e.g., transcript analysis, LLM agents)
- Oversee the full model lifecycle—from data ingestion and feature engineering to deployment, monitoring, and responsible AI practices
- Partner with product, engineering, and business leaders to define requirements, deliver value, and present insights to both executive and technical audiences
Other
- Manage, mentor, and grow a team of ~6 senior and mid-level data scientists
- Translate business needs into well-scoped data science problems and prioritize work to align with strategic goals
- Bachelor’s or Master’s in a quantitative field (e.g., Data Science, Computer Science, Engineering, Statistics, Physics)
- 6+ years in applied data science or ML roles, including 2+ years managing or mentoring other data scientists
- Strong communication skills and the ability to lead through influence in cross-functional environments
- Experience working in telecom, media, or subscription-based businesses
- Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.
