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EchoStar

Data Scientist I - Customer Lifecycle

Posted An Hour Ago
Be an Early Applicant
In-Office
Littleton, CO, USA
72K-103K Annually
Junior
In-Office
Littleton, CO, USA
72K-103K Annually
Junior
As a Data Scientist I, you'll transform customer lifecycle data into predictive models, focusing on churn prediction and lifetime value, while collaborating with teams on AI tools and dashboards.
The summary above was generated by AI
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.
The primary challenge in this role centers on transforming raw customer lifecycle data into intelligent, predictive engines that drive retention and optimize user experiences. Developing high-performing machine learning models is essential to uncovering hidden behavioral patterns, predicting churn, and calculating customer lifetime value. Additionally, this position tackles the integration of modern artificial intelligence, specifically through building applied AI tools like intelligent agents and chatbots to automate workflows and elevate engagement. Success requires seamless collaboration across data engineering and analytics teams to operationalize these models and translate technical outputs into actionable business strategies.
What Success Looks Like (Objectives)
  • Develop, train, and validate machine learning models focused on key customer lifecycle events, including churn prediction and lifetime value, to directly improve departmental retention OKRs
  • Extract and transform complex, large-scale data from the data warehouse to engineer high-quality features that measurably increase model accuracy and business relevance
  • Leverage generative AI frameworks and large language models (LLMs) to design and deploy internal intelligent agents and conversational chatbots that automate operational tasks
  • Translate sophisticated model outputs and predictive analytics into clear, actionable business strategies, partnering with analysts to design rigorous A/B tests
  • Monitor the post-deployment performance of all live models, proactively identifying data drift and executing model retraining cycles to adapt to evolving customer behaviors
  • Design and build interactive dashboards that visualize the tangible, data-driven outcomes of machine learning and AI initiatives for cross-functional stakeholders

Skills, Experience and Requirements
Core Skills and Competencies (What you'll bring)
  • Strong proficiency in Python for complex data manipulation and statistical modeling, combined with advanced SQL capabilities for large-scale data extraction
  • Deep understanding of traditional machine learning algorithms, including regression, classification, and tree-based models, along with their respective evaluation metrics
  • AI Literacy and Application skills, specifically a foundational understanding of LLMs, prompt engineering, and modern generative AI frameworks to build intelligent tools
  • Expertise in data visualization and data interpretation, utilizing tools like Tableau or Power BI to translate complex technical findings into intuitive dashboards
  • Critical experience in building, validating, and deploying predictive models within a professional or intensive applied academic environment
  • Excellent problem-solving, collaboration, and technical communication skills, with a natural curiosity to troubleshoot complex code and clearly document processes

Additional Qualifications
  • Familiarity with modern cloud data stack environments such as Snowflake, Databricks, Spark, AWS, or GCP
  • A Master's degree in a quantitative field with strong applied academic or internship experience in data science

Minimum Requirements
  • Minimum Education: Bachelor's Degree in Data Science, Statistics, Computer Science, Mathematics, or a highly quantitative field
  • Minimum Experience: 1 year of professional data science experience, or a Master's degree in a quantitative field with applied academic/internship experience
  • Required Technical Skills:
    • Python for data manipulation and modeling
    • SQL for data extraction
    • Traditional ML algorithms and evaluation metrics

Visa sponsorship not available for this role
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: EchoStar 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 )
HQ

EchoStar Englewood, Colorado, USA Office

EchoStar Corporate Headquarters - Meridian Office

9601 S Meridian Boulevard, Englewood, CO, United States, 80112

EchoStar Denver, Colorado, USA Office

EchoStar Downtown Denver Office - DGC Office

1615 17th St., Denver, CO, United States, 80202

EchoStar Littleton, Colorado, USA Office

EchoStar Wireless Headquarters - Riverfront Office

5701 S Santa Fe Dr., Littleton, CO, United States, 80120

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