Job Duties and ResponsibilitiesCandidates 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 RequirementsCore 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, BigQuery, 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, BigQuery, or Redshift
Salary RangesCompensation: $126,615.00/Year - $208,035.00/Year
BenefitsWe 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.
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.
