Decision Scientist

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
We are seeking a Decision Scientist to drive intelligence across our sales and retention channels (Boost Mobile stores, eCommerce, Amazon, Telesales, and B2B). This is role fusion of data analytics, data science, and strategy. In this role, you will move beyond reporting what happened to explaining why it happened and predicting what will happen next. You will serve as a technical bridge, utilizing statistical methods, predictive churn modeling, and Generative AI to enhance our customer lifecycle strategy. Your leadership will be crucial in transforming raw data into a roadmap for customer retention and revenue growth.
Key Responsibilities:

• Executive Communication & Data Storytelling
• Strategic Narrative: Act as the primary translator of complex statistical findings for the C-Suite and non-technical leadership
• Impact Visualization: Move beyond basic charts to create visual data stories that highlight the "So What?" and "Now What?" of the analysis; specifically, guide leadership on budget allocation for acquisition vs. retention based on data evidence
• ROI Demonstration: Regularly present findings in high-stakes meetings, clearly demonstrating how data science models are directly impacting revenue, churn reduction, and Net Promoter Scores (NPS/CSAT)
• Predictive Churn Modeling & Retention Strategy
• Proactive Retention: Evolve retention strategies from reactive reporting to proactive prediction. Build and maintain predictive churn models (using Python/R/XGBoost) to identify at-risk customers before they leave
• Survival Analysis: Analyze survival curves and hazard rates to pinpoint specific lifecycle moments (e.g., Day 90, Month 12) where customers are most vulnerable to churn
• Intervention Testing: Partner with marketing and retention teams to design and test targeted interventions based on individual churn probability scores
• AI Innovation & LLM Prototyping
• Unstructured Data Mining: Leverage Large Language Models (LLMs) and NLP techniques to analyze unstructured text data (e.g., chat logs, survey verbatims, telesales transcripts) to identify sentiment shifts and emerging churn drivers
• PoC Development: Act as a "prototyper" for the engineering team. You will build initial Proof-of-Concept (PoC) models locally to solve immediate business problems, then collaborate with engineers to scale successful models into production
• Advanced Lifecycle & Segmentation Analysis
• Dynamic Personas: Perform unsupervised learning (clustering/segmentation) on demographic, behavioral, and transactional data to create living customer personas
• CLV Optimization: Conduct Customer Lifetime Value (CLV) analysis to help the business prioritize high-value segments for white-glove service or exclusive offers
• Journey Mapping: Map the end-to-end customer journey to identify friction points that lead to early drop-off or failed activations
• Data Infrastructure & Visualization
• Cloud-Native Analytics: Write complex SQL queries to wrangle and join distinct datasets from sales, marketing, and web tracking sources within a cloud environment
• Automated Intelligence: Build automated, interactive dashboards (Tableau) that incorporate statistical baselines, trend lines, and automated forecast alerts
• Continuous Improvement
• Stay abreast of industry trends, best practices, and emerging technologies in sales analytics and AI. Proactively seek out opportunities to upgrade our sales channel analysis methodologies

Skills, Experience and Requirements
Education and Experience:

• Master's degree in Statistics, Computer Science, Data Science, or a quantitative business field
• 1-3 years in an advanced analytics role with a focus on customer behavior

Skills and Qualifications:

• Statistical Depth: Practical application of regression (Linear/Logistic), K-Means clustering, A/B testing, and Uplift Modeling
• Communication: Exceptional presentation skills with a portfolio demonstrating the ability to turn complex data into strategic business recommendations
• Database: SQL skills (Window functions, CTEs, complex joins)
• Cloud Computing (AWS): Experience working within the AWS ecosystem is required. Specifically S3 (storage), Athena (SQL querying), and familiarity with SageMaker or Lambda for automating analysis scripts
• Generative AI & NLP: Practical experience applying LLM APIs (e.g., OpenAI, Gemini, Hugging Face, or Llama) to business problems, such as text summarization, sentiment analysis, or entity extraction
• Coding: Proficiency in Python or R is required for statistical modeling (pandas, scikit-learn) and API integration
• Visualization: Strong experience with Tableau, PowerBI, or Looker

Salary Ranges
Compensation: $72,400.00/Year - $103,400.00/Year
Benefits
We offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: DISH Benefits .
The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location.
Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check. Our company is committed to fostering an inclusive and equitable workplace where every individual has the opportunity to succeed. We are dedicated to providing individuals with criminal or arrest records a fair chance of employment in accordance with local, state, and federal laws.
The posting will be active for a minimum of 3 days. The active posting will continue to extend by 3 days until the position is filled.
We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. EchoStar will accommodate the sincerely held religious beliefs of employees if such accommodations are not undue hardships and are otherwise within the bounds of applicable law. All qualified applicants with arrest or conviction records will be considered for employment in accordance with local, state, and federal law. You may redact any information that identifies age, date of birth, or dates of school/graduation from your application documents before submission and throughout our application process.
EchoStar will provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities, unless doing so poses an undue hardship on the Company, poses a direct threat of substantial harm to others, or is otherwise not required by law. EchoStar has a more detailed Accommodation Policy that applies to employees. EchoStar endeavors to make echostar.com and jobs.echostar.com accessible to users. Please contact [email protected] if you would like to discuss the accessibility of our website or need assistance completing the application process. This contact information is for accommodation requests only; do not use this contact information to inquire about the status of applications.
Click the links to access the following statements: EEO Policy Statement , Pay Transparency , EEOC Know Your Rights ( English / Spanish )