Company Summary

Echo Star 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 Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow.

Job Duties and Responsibilities

Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.

As a Staff Data Scientist in our AI Office, you will bridge the gap between complex data science and tangible business outcomes. You are responsible for solving the challenge of identifying high-impact AI opportunities and determining their feasibility within our vast data ecosystem. By transforming large-scale structured and unstructured data into production-grade GenAI and machine learning solutions, you will ensure our AI products drive measurable value for our customers and the mission.

What Success Looks Like (Objectives)

• Partner with stakeholders to identify high-impact, feasible opportunities for the AI Office and demonstrate how data science can drive business outcomes

• Deliver production-ready machine learning models for customer segmentation, churn prediction, and lifetime value estimation to directly impact department OKRs

• Architect and deploy GenAI and LLM solutions that automate complex workflows, such as transcript analysis and compliance validation, using cutting-edge AI applications

• Lead the transformation of large-scale structured and unstructured data into actionable insights that inform product strategy and user modeling

• Collaborate with cross-functional teams to build scalable, cloud-based solutions while providing technical mentorship to elevate the team's collective expertise

• Master the art of storytelling by communicating complex models and findings to both technical and non-technical audiences via intuitive dashboards and presentations

Skills, Experience and Requirements

Core Skills and Competencies (What you’ll bring)

• You don't just design models; you champion them by balancing immediate feature requests against long-term technical health and the elimination of technical debt in production environments

• Expert-level mastery of statistical modeling and machine learning—including regression, clustering, and neural networks—with the ability to design and analyze rigorous A/B tests and controlled experiments

• Advanced proficiency in building and deploying LLM-based solutions, demonstrating a deep understanding of prompt engineering and the management of unstructured data (text and images)

• Skilled in Python and SQL for building robust data pipelines and preprocessing large-scale datasets using big data tools like Spark, Big Query, or Redshift

• A proven ability to analyze ambiguous information, make rational judgments regarding model architecture, and take responsibility for the results in a fast-paced environment

• Strong ability to build working relationships across teams to achieve shared goals, while utilizing enterprise platforms like AWS, Databricks, or Dataiku to maintain ML systems

• Excellence in writing clearly and succinctly for diverse audiences, ensuring that technical findings are translated into an inspiring vision for stakeholders

Additional Qualifications

• Experience with enterprise-level AI governance and compliance

• Familiarity with emerging trends in multimodal AI and agentic workflows

Minimum Requirements

• Bachelor’s degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field

• 6+ years of experience in data science and applied machine learning with a proven track record of delivering business impact

• Must have at least 6 years of experience with:

Python and SQL for data science and pipeline development

• AWS or similar cloud-based enterprise platforms (Databricks, Dataiku)

• Big Data tools such as Spark, Big Query, or Redshift

Salary Ranges

Compensation: $153,755.00/Year - $208,035.00/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: Echo Star 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. Echo Star 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.

Echo Star 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. Echo Star has a more detailed Accommodation Policy that applies to employees. Echo Star endeavors to make echostar.com and jobs.echostar.com accessible to users. Please contact leaves@dish.com 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)

Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.

As a Staff Data Scientist in our AI Office, you will bridge the gap between complex data science and tangible business outcomes. You are responsible for solving the challenge of identifying high-impact AI opportunities and determining their feasibility within our vast data ecosystem. By transforming large-scale structured and unstructured data into production-grade GenAI and machine learning solutions, you will ensure our AI products drive measurable value for our customers and the mission.

What Success Looks Like (Objectives)

• Partner with stakeholders to identify high-impact, feasible opportunities for the AI Office and demonstrate how data science can drive business outcomes

• Deliver production-ready machine learning models for customer segmentation, churn prediction, and lifetime value estimation to directly impact department OKRs

• Architect and deploy GenAI and LLM solutions that automate complex workflows, such as transcript analysis and compliance validation, using cutting-edge AI applications

• Lead the transformation of large-scale structured and unstructured data into actionable insights that inform product strategy and user modeling

• Collaborate with cross-functional teams to build scalable, cloud-based solutions while providing technical mentorship to elevate the team's collective expertise

• Master the art of storytelling by communicating complex models and findings to both technical and non-technical audiences via intuitive dashboards and presentations

Core Skills and Competencies (What you’ll bring)

• You don't just design models; you champion them by balancing immediate feature requests against long-term technical health and the elimination of technical debt in production environments

• Expert-level mastery of statistical modeling and machine learning—including regression, clustering, and neural networks—with the ability to design and analyze rigorous A/B tests and controlled experiments

• Advanced proficiency in building and deploying LLM-based solutions, demonstrating a deep understanding of prompt engineering and the management of unstructured data (text and images)

• Skilled in Python and SQL for building robust data pipelines and preprocessing large-scale datasets using big data tools like Spark, Big Query, or Redshift

• A proven ability to analyze ambiguous information, make rational judgments regarding model architecture, and take responsibility for the results in a fast-paced environment

• Strong ability to build working relationships across teams to achieve shared goals, while utilizing enterprise platforms like AWS, Databricks, or Dataiku to maintain ML systems

• Excellence in writing clearly and succinctly for diverse audiences, ensuring that technical findings are translated into an inspiring vision for stakeholders

Additional Qualifications

• Experience with enterprise-level AI governance and compliance

• Familiarity with emerging trends in multimodal AI and agentic workflows

Minimum Requirements

• Bachelor’s degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field

• 6+ years of experience in data science and applied machine learning with a proven track record of delivering business impact

• Must have at least 6 years of experience with:

Python and SQL for data science and pipeline development

• AWS or similar cloud-based enterprise platforms (Databricks, Dataiku)

• Big Data tools such as Spark, Big Query, or Redshift