> Markdown version of [/jobs/ext/4028264-senior-data-scientist-ai-analytics](https://www.wearedevelopers.com/jobs/ext/4028264-senior-data-scientist-ai-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Scientist, AI Analytics

- **Company:** ECHOSTAR
- **Location:** Denver, CO, United States
- **Experience:** Expert
- **Salary:** $96,250.0 - $137,500.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Audit Trail, Cloud Engineering, Continuous Delivery, Distributed Data Store, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Standard Sql, Scala (Programming Language), SQL Databases, Unstructured Data, Pytorch, Large Language Models, Snowflake, Prompt Engineering, Model Validation, Scikit Learn, Information Technology, Data Analytics, Data Management, Machine Learning Operations, Software Library, Databricks
- **Published:** October 30, 2026
- **Apply:** https://www.denverjobsite.com/job.asp?id=3480968237&tx=JR11407LFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Proven capability in designing, deploying, and maintaining production-grade predictive machine learning models, including classification, regression, and time-series forecasting
 * Applied AI proficiency in prompt engineering, model validation, and deployment of large language models within production environments
 * Strong technical capabilities in Python, Scala, and SQL, coupled with hands-on proficiency in machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch
 * Ability to design and optimize distributed data science pipelines within enterprise cloud platforms such as AWS, Databricks, or Snowflake
 * Deep expertise in experimental design, causal inference, and rigorous A/B testing methodologies to validate algorithmic impact against critical business metrics
 * Collaborative problem-solving and communication skills to convey statistical findings and technical roadmaps to cross-functional stakeholders and leadership

Candidates must be willing to participate in at least one in-person interview., * Minimum Education: Bachelor's Degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field

 * Minimum Experience: 4 years of experience in data science and applied machine learning
 * Required Technical Skills: Must have at least 4 years of experience with:
 * Python, Scala, and SQL
 * Machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch
 * Cloud-based AI and data platforms such as AWS, Databricks, or Snowflake
 * Unstructured data processing for natural language processing (NLP) or generative AI workflows

## Description

* Partner with operational and engineering leaders to establish machine learning roadmaps that align with enterprise OKRs and product objectives
 * Design, deploy, and maintain scalable production machine learning systems for customer segmentation, predictive churn mitigation, and lifetime value optimization
 * Implement and scale generative AI initiatives by engineering robust LLM-assisted workflows for automated multi-channel transcript analysis and real-time compliance auditing
 * Establish automated data science pipelines across enterprise cloud infrastructures to support model reproducibility, auditability, and continuous delivery
 * Leverage AI developer tooling and automated monitoring frameworks to optimize model training efficiency, track pipeline latency, and streamline deployment cycles
 * Translate complex model outputs into analytical dashboards and actionable recommendations that inform operational decisions across core business units