Data Scientist - AI Products

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.
• Transform 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, 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.
• 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.

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.