Data Scientist I - Customer Lifecycle

Company Summary EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV. Department Summary Our Retail Wireless team, serving our Boost Mobile and Gen Mobile brands, is redefining consumer expectations through new platforms, new business models and new ways of thinking. Equipped with a passion for change and the power to drive it, we continue to push boundaries and be a disruptive force in the market. Job Duties and Responsibilities Candidates must be willing to participate in at least one in-person interview.   This role focuses on understanding and optimizing the customer lifecycle through rigorous data-driven analysis and insights. The successful candidate tackles key business problems surrounding customer retention, lifetime value, and engagement by building robust reporting solutions and conducting deep-dive analyses. Working at the intersection of business strategy and technical execution, this position translates complex datasets into actionable recommendations that directly influence retention strategies. By bridging the gap between raw data and business stakeholders, this role ensures accurate reporting and supports broader data science initiatives across the enterprise.   What Success Looks Like (Objectives): Own and execute analytical projects, translating business problems into actionable customer lifecycle strategies and data-driven recommendations Conduct deep-dive statistical analysis—specifically churn driver analysis and program impact analysis—to evaluate how various campaigns and changes affect customer retention behaviors Build and deploy scalable, algorithmic pipelines that translate customer milestones, engagement metrics, and LTV into automated retention interventions, moving beyond static visibility to drive direct business impact Architect and deploy automated data pipelines and scalable feature engineering frameworks directly within Databricks and Snowflake, partnering closely with Data Science and Engineering to operationalize AI models Collaborate with Data Scientist to architect, train, and deploy predictive machine learning models (such as proprietary churn and LTV algorithms) in production to drive automated, proactive business solutions Document analytical processes and code to ensure long-term scalability and share knowledge with the broader analytics team Skills, Experience and Requirements Core Skills and Competencies (What you’ll bring): Strong proficiency in querying complex datasets using SQL alongside statistical analysis capabilities in Python or R Hands-on experience performing data transformation and querying within Snowflake or Databricks environments Solid expertise in data visualization, specifically in designing high-impact interactive dashboards using Tableau, Power BI, or similar platforms Strong analytical thinking and statistical reasoning to interpret complex datasets and translate them into actionable business insights Excellent communication and data storytelling abilities to convey analytical findings clearly to non-technical business partners and stakeholders Practical AI literacy and application skills, demonstrating the ability to leverage AI-assisted development tools to optimize analytical workflows   Additional Qualifications: Prior domain experience in customer lifecycle analytics, customer experience (CX), finance, or marketing analytics is highly preferred Master's degree in a quantitative field such as Business Analytics, Statistics, Data Science, Computer Science, Economics, or Mathematics is a plus   Minimum Requirements: Bachelor’s Degree in a quantitative field (such as Business Analytics, Statistics, Data Science, Computer Science, Economics, Mathematics, or a related field) 1-2+ years of experience in Data Science,