Senior Data Scientist - AI Products

About the Role

Key Responsibilities

• Partner with stakeholders to identify high-impact, feasible opportunities and demonstrate how data science can drive business outcomes.
• Develop machine learning models for customer segmentation, churn prediction, user modeling, and lifetime value estimation.
• Design and deploy GenAI and LLM solutions to automate complex workflows, such as transcript analysis and compliance validation.
• Transform and analyze large-scale structured and unstructured data (e.g., text, images) to uncover actionable insights.
• Collaborate with cross-functional teams to build and deploy scalable, cloud-based data science and GenAI solutions; provide technical mentorship.
• Communicate complex models and findings to both technical and non-technical audiences via dashboards, notebooks, and presentations.

Requirements

• Bachelor's or Master's degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field.
• 4+ years of experience in data science and applied machine learning, with a proven track record of delivering business impact from data-driven solutions.
• Strong foundation in statistical and machine learning techniques, including regression, classification, clustering, neural networks, and ensemble models.
• Proficient in Python and SQL for data science workflows; skilled in building and evaluating generative AI and LLM-based solutions.
• Experienced in prompt engineering, model evaluation, and deploying LLMs in production environments.
• Skilled in processing unstructured data (text, images) using modern ML/DL frameworks.
• Proven ability to design, run, and analyze A/B tests and controlled experiments.
• Hands-on experience with AWS cloud environments and enterprise-scale ML platforms like Dataiku and Databricks.

Nice to Have

• Master's or PhD in a relevant quantitative domain.
• Experience with big data tools such as Amazon Athena, Redshift, BigQuery, Spark, or Teradata.
• Familiarity with MLOps practices for deploying, monitoring, and maintaining ML/GenAI systems in production.
• Data engineering skills for preprocessing, cleaning, and transforming large-scale datasets.

Qualifications

• Educational background in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or related fields.
• 4+ years of experience in data science and applied machine learning.

Benefits & Perks

• Versatile health perks, including flexible spending accounts, HSA, and a 401(k) Plan with company match.
• ESPP, career opportunities, and a flexible time away plan.
• All benefits can be viewed at DISH Benefits.
• Compensation varies based on qualifications, skill level, and work location.
• Candidates must complete pre-employment screening, which may include drug testing and DMV checks.