EchoStar is seeking to reimagine the future of connectivity through AI and data science solutions to drive business outcomes across its brands, including customer segmentation, churn prediction, and automation of complex workflows.
Requirements
- Bachelor’s or Master’s degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field
- Master’s or PhD in a relevant quantitative domain
- 4+ years of experience in data science and applied machine learning, with a proven track record of delivering business impact from data-driven solutions
- Experience with big data tools such as Amazon Athena, Redshift, BigQuery, Spark, or Teradata
- Experienced in prompt engineering, model evaluation, and deploying LLMs in production environments
- Hands-on experience with AWS cloud environments and enterprise-scale ML platforms like Dataiku and Databricks
- Strong foundation in statistical and machine learning techniques, including regression, classification, clustering, neural networks, and ensemble models
Responsibilities
- Partner with stakeholders to identify high-impact, feasible opportunities for the AI Office and demonstrate how data science can drive business outcomes
- Develop machine learning models for customer segmentation, churn prediction, user modeling, and lifetime value estimation
- Design and deploy GenAI and LLM solutions to automate complex workflows, such as transcript analysis and compliance validation
- Transform and analyze large-scale structured and unstructured data (e.g., text, images) to uncover actionable insights
- Collaborate with cross-functional teams to build and deploy scalable, cloud-based data science and GenAI solutions; provide technical mentorship
- Communicate complex models and findings to both technical and non-technical audiences via dashboards, notebooks, and presentations
Other
- Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session
- Visa sponsorship not available for this role
- Bachelor’s or Master’s degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field
- Master’s or PhD in a relevant quantitative domain
- Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check
