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.

Drive the strategic evaluation and deployment of advanced AI architectures to solve complex multi-brand operational challenges through statistical rigor and predictive modeling. Design sophisticated agentic AI pipelines and governance frameworks that ensure model reliability across cloud-native and on-premises environments. Bridge the gap between raw data and business strategy by delivering high-fidelity simulations and benchmarks that directly improve subscriber growth and network efficiency.

What Success Looks Like (Objectives)

• Optimize model performance and cost-efficiency by benchmarking trade-offs between cloud-native and on-premises execution pathways for large-scale deployments

• Lead the design and statistical validation of multi-agent architectures using Lang Graph and AWS Bedrock to achieve autonomous provisioning and Level 4 autonomy

• Enhance network efficiency through the development of high-accuracy predictive models for churn, anomaly detection, and time-series forecasting

• Ensure model robustness and long-term validity by implementing automated experiment tracking, versioning, and drift detection via Databricks Unity Catalog

• Translate complex data science outputs into actionable executive scorecards that guide long-term business strategy and vendor RFI/RFP evaluations

• Maintain enterprise-wide model integrity by aligning federated AI governance with NIST AI RMF and TOGAF standards using "Digital Twin" policy simulations

Skills, Experience and Requirements

Core Skills and Competencies (What you’ll bring)

• Advanced proficiency in AI innovation, specifically the application of agentic frameworks like Lang Chain or Lang Graph to solve autonomous operation problems

• Strong expertise in machine learning development using Python, Py Torch, and Tensor Flow to build models with high predictive power and statistical reliability

• Critical experience in LLM deployment strategies, including RAG optimization, fine-tuning, and performance inference across hybrid cloud environments

• Deep understanding of MLOps lifecycle management within modern data platforms like Databricks or Sage Maker to ensure scalable model delivery

• Collaborative professional expertise in data storytelling, enabling the translation of complex quantitative findings into clear strategic recommendations for C-suite stakeholders

• Thorough knowledge of AI governance and responsible AI principles to mitigate model risk and ensure ethical data application

Additional Qualifications

• Familiarity with TM Forum ODA or telecom-specific data models

• Exposure to on-premises AI infrastructure, including GPU cluster provisioning or K8s platforms

• Background in knowledge graphs or enterprise search optimization

Minimum Requirements

• Minimum Education:

Bachelor’s Degree in Computer Science, Data Science, Statistics, Electrical Engineering, or a related quantitative field

• Minimum Experience:

5 years of experience in data science

• Required Technical Skills:

Must have at least 2 years of experience with:

• Python (Scikit-learn, Py Torch, or Tensor Flow)

• Databricks, Spark, or AWS (Sage Maker/Bedrock)

• SQL and cloud-native orchestration (dbt or Airflow)

Salary Ranges

Compensation: $96,250.00/Year - $125,125.00/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. 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.

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 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.

Drive the strategic evaluation and deployment of advanced AI architectures to solve complex multi-brand operational challenges through statistical rigor and predictive modeling. Design sophisticated agentic AI pipelines and governance frameworks that ensure model reliability across cloud-native and on-premises environments. Bridge the gap between raw data and business strategy by delivering high-fidelity simulations and benchmarks that directly improve subscriber growth and network efficiency.

What Success Looks Like (Objectives)

• Optimize model performance and cost-efficiency by benchmarking trade-offs between cloud-native and on-premises execution pathways for large-scale deployments

• Lead the design and statistical validation of multi-agent architectures using Lang Graph and AWS Bedrock to achieve autonomous provisioning and Level 4 autonomy

• Enhance network efficiency through the development of high-accuracy predictive models for churn, anomaly detection, and time-series forecasting

• Ensure model robustness and long-term validity by implementing automated experiment tracking, versioning, and drift detection via Databricks Unity Catalog

• Translate complex data science outputs into actionable executive scorecards that guide long-term business strategy and vendor RFI/RFP evaluations

• Maintain enterprise-wide model integrity by aligning federated AI governance with NIST AI RMF and TOGAF standards using "Digital Twin" policy simulations

Core Skills and Competencies (What you’ll bring)

• Advanced proficiency in AI innovation, specifically the application of agentic frameworks like Lang Chain or Lang Graph to solve autonomous operation problems

• Strong expertise in machine learning development using Python, Py Torch, and Tensor Flow to build models with high predictive power and statistical reliability

• Critical experience in LLM deployment strategies, including RAG optimization, fine-tuning, and performance inference across hybrid cloud environments

• Deep understanding of MLOps lifecycle management within modern data platforms like Databricks or Sage Maker to ensure scalable model delivery

• Collaborative professional expertise in data storytelling, enabling the translation of complex quantitative findings into clear strategic recommendations for C-suite stakeholders

• Thorough knowledge of AI governance and responsible AI principles to mitigate model risk and ensure ethical data application

Additional Qualifications

• Familiarity with TM Forum ODA or telecom-specific data models

• Exposure to on-premises AI infrastructure, including GPU cluster provisioning or K8s platforms

• Background in knowledge graphs or enterprise search optimization

Minimum Requirements

• Minimum Education:

Bachelor’s Degree in Computer Science, Data Science, Statistics, Electrical Engineering, or a related quantitative field

• Minimum Experience:

5 years of experience in data science

• Required Technical Skills:

Must have at least 2 years of experience with:

• Python (Scikit-learn, Py Torch, or Tensor Flow)

• Databricks, Spark, or AWS (Sage Maker/Bedrock)

• SQL and cloud-native orchestration (dbt or Airflow)